PhD student: 2017 ~ Present
URL: https://haolibai.github.io/
Email: hlbai@cse.cuhk.edu.hk

1. “Revisiting Parameter Sharing for Automatic Neural Channel Number Search,” Jiaxing Wang*, Haoli Bai*, Jiaxiang Wu, Xupeng Shi, Junzhou Huang, Irwin King, Michael R. Lyu, Jian Cheng, in Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS2020), pp. 1-12, Vancouver, Canada, December 6 - December 12, 2020.
   Paper [ML]
   
   
2. “Few Shot Network Compression via Cross Distillation,” Haoli Bai, Jiaxiang Wu, Irwin King, Michael R. Lyu, in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI2020), pp. 3203-3210, New York, USA, February 7 - February 12, 2020.
   Paper [ML]
   
   
3. “Neural Relational Topic Models for Scientific Article Analysis,” Haoli Bai, Zhuangbin Chen, Michael R. Lyu, Irwin King, Zenglin Xu, in Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM2018), pp. 27-36, Torino, Italy, October 22 - October 26, 2018.
   Paper [ML]
   
   

PhD student: 2017 ~ Present
URL: http://www.cse.cuhk.edu.hk/~lijj
Email: lijj@cse.cuhk.edu.hk

1. “Unsupervised Text Generation by Learning from Search,” Jingjing Li, Zichao Li, Lili Mou, Xin Jiang, Michael R. Lyu, Irwin King, in Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS2020), pp. 1-12, Vancouver, Canada, December 6 - December 12, 2020.
   Paper [ML]
   
   
2. “Improving Question Generation with to the Point Context,” Jingjing Li, Yifan Gao, Lidong Bing, Irwin King, Michael R. Lyu, in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP/IJCNLP2019), pp. 3214-3224, Hong Kong, China, November 3 - November 7, 2019.
   Paper [ML]
   
   

PhD student: 2017 ~ Present
URL: https://wxjiao.github.io/
Email: wxjiao@cse.cuhk.edu.hk

1. “Data Rejuvenation: Exploiting Inactive Training Examples for Neural Machine Translation,” Wenxiang Jiao, Xing Wang, Shilin He, Irwin King, Michael R. Lyu, Zhaopeng Tu, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 2255-2266, Online, USA, November 16 - November 20, 2020.
   Paper [ML]
   
   
2. “Exploiting Unsupervised Data for Emotion Recognition in Conversations,” Wenxiang Jiao, Michael R. Lyu, Irwin King, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP (EMNLP-Findings2020), pp. 4839-4846, Online, USA, November 16 - November 20, 2020.
   Paper [ML]
   
   
3. “Real-Time Emotion Recognition via Attention Gated Hierarchical Memory Network,” Wenxiang Jiao, Michael R. Lyu, Irwin King, in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI2020), pp. 8002-8009, New York, USA, February 7 - February 12, 2020.
   Paper [ML]
   
   
4. “HiGRU: Hierarchical Gated Recurrent Units for Utterance-Level Emotion Recognition,” Wenxiang Jiao, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT2019), pp. 397-406, Minneapolis, USA, June 2 - June 7, 2019.
   Paper [ML]
   
   

PhD student: 2017 ~ Present
URL: http://www.cse.cuhk.edu.hk/~wbwu
Email: wbwu@cse.cuhk.edu.hk

1. “Boosting the Transferability of Adversarial Samples via Attention,” Weibin Wu, Yuxin Su, Xixian Chen, Shenglin Zhao, Irwin King, Michael R. Lyu, Yu-Wing Tai, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 1158-1167, Seattle, USA, June 13 - June 19, 2020.
   Paper [MM]
   
   
2. “Towards Global Explanations of Convolutional Neural Networks With Concept Attribution,” Weibin Wu, Yuxin Su, Xixian Chen, Shenglin Zhao, Irwin King, Michael R. Lyu, Yu-Wing Tai, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 8649-8658, Seattle, USA, June 13 - June 19, 2020.
   CVPR 2020 Oral Presentation
   Paper [MM]
   
   
3. “Deep Validation: Toward Detecting Real-World Corner Cases for Deep Neural Networks,” Weibin Wu, Hui Xu, Sanqiang Zhong, Michael R. Lyu, Irwin King, in Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2019), pp. 125-137, Portland, USA, June 24 - June 27, 2019.
   Paper [SE]
   
   

PhD student: 2017 ~ Present
URL: https://yifan-gao.github.io/
Email: yfgao@cse.cuhk.edu.hk

1. “Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading,” Yifan Gao, Chien-Sheng Wu, Jingjing Li, Shafiq Joty, Steven C. H. Hoi, Caiming Xiong, Irwin King, Michael R. Lyu, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 2439-2449, Online, USA, November 16 - November 20, 2020.
   Paper [ML]
   
   
2. “Dialogue Generation on Infrequent Sentence Functions via Structured Meta-Learning,” Yifan Gao, Piji Li, Wei Bi, Xiaojiang Liu, Michael R. Lyu, Irwin King, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP (EMNLP-Findings2020), pp. 431-440, Online, USA, November 16 - November 20, 2020.
   Paper [ML]
   
   
3. “Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading,” Yifan Gao, Chien-Sheng Wu, Shafiq R. Joty, Caiming Xiong, Richard Socher, Irwin King, Michael R. Lyu, Steven C. H. Hoi, in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL2020), pp. 935-945, Online, USA, Jul 5, 2020 - Jul 10, 2020.
   Paper [ML]
   
   
4. “Difficulty Controllable Generation of Reading Comprehension Questions,” Yifan Gao, Lidong Bing, Wang Chen, Michael R. Lyu, Irwin King, in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI2019), pp. 4968-4974, Macao, China, August 10 - August 16, 2019.
   Paper [ML]
   
   
5. “Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling,” Yifan Gao, Piji Li, Irwin King, Michael R. Lyu, in Proceedings of the 57th Conference of the Association for Computational Linguistics (ACL2019), pp. 4853-4862, Florence, Italy, July 28 - August 2, 2019.
   Paper [ML]
   
   
6. “Generating Distractors for Reading Comprehension Questions from Real Examinations,” Yifan Gao, Lidong Bing, Piji Li, Irwin King, Michael R. Lyu, in Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI2019), pp. 6423-6430, Honolulu, USA, January 27 - February 1, 2019.
   Paper [ML]
   
   

PhD student: 2018 ~ Present
URL: http://www.cse.cuhk.edu.hk/~tyyang
Email: tyyang@cse.cuhk.edu.hk

PhD student: 2018 ~ Present
URL: http://www.cse.cuhk.edu.hk/~zbchen
Email: zbchen@cse.cuhk.edu.hk

1. “Towards Intelligent Incident Management: Why We Need It and How We Make It,” Zhuangbin Chen, Yu Kang, Hongyu Zhang, Hui Xu, Li Yang, Zhangwei Xu, Pu Zhao, Michael R. Lyu, in Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2020), pp. 1487-1497, Online, USA, November 8 - November 13, 2020.
   Paper [SE]
   
   

PhD student: 2019 ~ Present
URL: http://www.cse.cuhk.edu.hk/~wcgu
Email: wcgu@cse.cuhk.edu.hk

PhD student: 2020 ~ Present
URL: http://www.cse.cuhk.edu.hk/~jyliu
Email: jyliu@cse.cuhk.edu.hk

1. “Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression,” Jinyang Liu, Jieming Zhu, Shilin He, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering (ASE2019), pp. 863-873, San Diego, USA, November 11 - November 15, 2019.
   Paper [SE]
   
   

PhD student: 2020 ~ Present
URL: http://www.cse.cuhk.edu.hk/~jcshen
Email: jcshen@cse.cuhk.edu.hk

PhD student: 2020 ~ Present
URL: https://penguinnnnn.github.io/
Email: jthuang@cse.cuhk.edu.hk

PhD student: 2020 ~ Present
URL: https://www.yunpeng.work/
Email: ypeng@cse.cuhk.edu.hk

PhD student: 2020 ~ Present
URL: https://yintonghuo.github.io/yintonghuo/
Email: ythuo@cse.cuhk.edu.hk

PhD student: 2020 ~ Present
URL: http://www.cse.cuhk.edu.hk/~jpzhang
Email: jpzhang@cse.cuhk.edu.hk

PhD student: 2020 ~ Present
URL: https://scholar.google.com/citations?user=4v5x0bUAAAAJ&hl=en
Email: wxwang@cse.cuhk.edu.hk

Graduated in 2020
Researcher, Salesforce, Singapore
URL: https://yuewang-cuhk.github.io/
Email: yuewang@cse.cuhk.edu.hk

“Neural Keyphrase Generation for Social Media Understanding” Thesis Presentation

1. “VD-BERT: A Unified Vision and Dialog Transformer with BERT,” Yue Wang, Shafiq Joty, Michael R. Lyu, Irwin King, Caiming Xiong, S.C.H. Hoi, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 3325-3338, Online, USA, November 16 - November 20, 2020.
   Paper [ML]
   
   
2. “Cross-Media Keyphrase Prediction: A Unified Framework with Multi-Modality Multi-Head Attention and Image Wordings,” Yue Wang, Jing Li, Michael R. Lyu, Irwin King, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 3311-3324, Online, USA, November 16 - November 20, 2020.
   Paper [ML]
   
   
3. “Topic-Aware Neural Keyphrase Generation for Social Media Language,” Yue Wang, Jing Li, Hou Pong Chan, Irwin King, Michael R. Lyu, Shuming Shi, in Proceedings of the 57th Conference of the Association for Computational Linguistics (ACL2019), pp. 2516-2526, Florence, Italy, July 28 - August 2, 2019.
   Paper [ML]
   
   
4. “Microblog Hashtag Generation via Encoding Conversation Contexts,” Yue Wang, Jing Li, Irwin King, Michael R. Lyu, Shuming Shi, in Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT2019), pp. 1624-1633, Minneapolis, USA, June 2 - June 7, 2019.
   Paper [ML]
   
   
5. “Entropy-Based Service Selection with Uncertain QoS for Mobile Cloud Computing,” Yue Wang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 1st IEEE Conference on Collaboration and Internet Computing (CIC2015), pp. 252-259, Hangzhou, China, October 27 - October 30, 2015.
   Paper [DS]
   
   

Graduated in 2020
Researcher, Huawei, China
URL: https://ppliuboy.github.io/
Email: ppliu@cse.cuhk.edu.hk

“Self-Supervised Learning of Dense Correspondence” Thesis Presentation

1. “Learning 3D Face Reconstruction with a Pose Guidance Network,” Pengpeng Liu, Xintong Han, Michael R. Lyu, Irwin King, Jia Xu, in Proceedings of the 15th Asian Conference on Computer Vision (ACCV2020), pp. 154-169, Kyoto, Japan, November 30 - December 4, 2020.
   ACCV 2020 Oral Presentation
   Paper [MM]
   
   
2. “Flow2Stereo: Effective Self-Supervised Learning of Optical Flow and Stereo Matching,” Pengpeng Liu, Irwin King, Michael R. Lyu, Jia Xu, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 6647-6656, Seattle, USA, June 13 - June 19, 2020.
   Paper [MM]
   
   
3. “SelFlow: Self-Supervised Learning of Optical Flow,” Pengpeng Liu, Michael R. Lyu, Irwin King, Jia Xu, in Proceedings of the 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR2019), pp. 4571-4580, Long Beach, USA, June 16 - June 20, 2019.
   Paper [MM]
   
   
4. “DDFlow: Learning Optical Flow with Unlabeled Data Distillation,” Pengpeng Liu, Irwin King, Michael R. Lyu, Jia Xu, in Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI2019), pp. 8770-8777, Honolulu, USA, January 27 - February 1, 2019.
   Paper [ML]
   
   

Graduated in 2020
Researcher, Microsoft Research Asia, China
URL: https://shilinhe.github.io/
Email: slhe@cse.cuhk.edu.hk

“Interpretability Driven Intelligent Software Reliability Engineering” Thesis Presentation

1. “Towards Understanding Neural Machine Translation with Word Importance,” Shilin He, Zhaopeng Tu, Xing Wang, Longyue Wang, Michael R. Lyu, Shuming Shi, in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP/IJCNLP2019), pp. 953-962, Hong Kong, China, November 3 - November 7, 2019.
   Paper [ML]
   
   
2. “Identifying Impactful Service System Problems via Log Analysis,” Shilin He, Qingwei Lin, Jian-Guang Lou, Hongyu Zhang, Michael R. Lyu, Dongmei Zhang, in Proceedings of the 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2018), pp. 60-70, Lake Buena Vista, USA, November 4 - November 9, 2018.
   Paper [SE]
   
   
3. “Experience Report: System Log Analysis for Anomaly Detection,” Shilin He, Jieming Zhu, Pinjia He, Michael R. Lyu, in Proceedings of the 27th IEEE International Symposium on Software Reliability Engineering (ISSRE2016), pp. 207-218, Ottawa, Canada, October 23 - October 27, 2016.
   ISSRE 2019 30-Year Most Influential Papers
   Paper [SE]
   
   

Graduated in 2020
Researcher, Huawei Noah's Ark Lab, China
URL: https://jack57lee.github.io/
Email: jianli@cse.cuhk.edu.hk

“Effective Attention Mechanisms for Sequence Learning” Thesis Presentation

1. “Neuron Interaction Based Representation Composition for Neural Machine Translation,” Jian Li, Xing Wang, Baosong Yang, Shuming Shi, Michael R. Lyu, Zhaopeng Tu, in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI2020), pp. 8204-8211, New York, USA, February 7 - February 12, 2020.
   Paper [ML]
   
   
2. “Information Aggregation for Multi-Head Attention with Routing-by-Agreement,” Jian Li, Baosong Yang, Zi-Yi Dou, Xing Wang, Michael R. Lyu, Zhaopeng Tu, in Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT2019), pp. 3566-3575, Minneapolis, USA, June 2 - June 7, 2019.
   Paper [ML]
   
   
3. “Multi-Head Attention with Disagreement Regularization,” Jian Li, Zhaopeng Tu, Baosong Yang, Michael R. Lyu, Tong Zhang, in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP2018), pp. 2897-2903, Brussels, Belgium, October 31 - November 4, 2018.
   Paper [ML]
   
   
4. “Code Completion with Neural Attention and Pointer Networks,” Jian Li, Yue Wang, Michael R. Lyu, Irwin King, in Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI2018), pp. 4159-4165, Stockholm, Sweden, July 13 - July 19, 2018.
   Paper [ML]
   
   
5. “Software Defect Prediction via Convolutional Neural Network,” Jian Li, Pinjia He, Jieming Zhu, Michael R. Lyu, in Proceedings of the 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS2017), pp. 318-328, Prague, Czech Republic, July 25 - July 29, 2017.
   Paper [SE]
   
   

Graduated in 2019
Researcher, ByteDance Cooperation, China
URL: https://zengjichuan.github.io/
Email: jczeng@cse.cuhk.edu.hk

“Latent Variable Modeling for Natural Language Understanding” Thesis Presentation

1. “What You Say and How You Say It: Joint Modeling of Topics and Discourse in Microblog Conversations,” Jichuan Zeng, Jing Li, Yulan He, Cuiyun Gao, Michael R. Lyu, Irwin King, Transactions of the Association for Computational Linguistics (TACL), vol. 7, pp. 267-281, 2019.
   Paper [ML]
   
   

1. “Photon: A Robust Cross-Domain Text-to-SQL System,” Jichuan Zeng, Xi Victoria Lin, Steven C. H. Hoi, Richard Socher, Caiming Xiong, Michael R. Lyu, Irwin King, in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations (ACL:Demo2020), pp. 204-214, Online, USA, Jul 5, 2020 - Jul 10, 2020.
   Paper [ML]
   
   
2. “What Changed Your Mind: The Roles of Dynamic Topics and Discourse in Argumentation Process,” Jichuan Zeng, Jing Li, Yulan He, Cuiyun Gao, Michael R. Lyu, Irwin King, in Proceedings of The Web Conference 2020 (WWW2020), pp. 1502-1513, Taipei, Taiwan, April 20 - April 25, 2020.
   Paper [DS]
   
   
3. “Topic Memory Networks for Short Text Classification,” Jichuan Zeng, Jing Li, Yan Song, Cuiyun Gao, Michael R. Lyu, Irwin King, in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP2018), pp. 3120-3131, Brussels, Belgium, October 31 - November 4, 2018.
   Paper [ML]
   
   

Graduated in 2019
Postdoctoral fellow, The Chinese University of Hong Kong, China
URL: http://www.cse.cuhk.edu.hk/~yxsu
Email: yxsu@cse.cuhk.edu.hk

“Distributed Distance Learning Algorithms and Applications” Thesis Presentation

1. “Parallel Wasserstein Generative Adversarial Nets with Multiple Discriminators,” Yuxin Su, Shenglin Zhao, Xixian Chen, Irwin King, Michael R. Lyu, in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI2019), pp. 3483-3489, Macao, China, August 10 - August 16, 2019.
   Paper [ML]
   
   
2. “Communication-Efficient Distributed Deep Metric Learning with Hybrid Synchronization,” Yuxin Su, Michael R. Lyu, Irwin King, in Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM2018), pp. 1463-1472, Torino, Italy, October 22 - October 26, 2018.
   Paper [ML]
   
   
3. “Learning to Rank Using Localized Geometric Mean Metrics,” Yuxin Su, Irwin King, Michael R. Lyu, in Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2017), pp. 45-54, Tokyo, Japan, August 7 - August 11, 2017.
   Paper [ML]
   
   
4. “Distributed Information-Theoretic Metric Learning in Apache Spark,” Yuxin Su, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2016 IEEE International Joint Conference on Neural Networks (IJCNN2016), pp. 3306-3313, Vancouver, Canada, July 24 - July 29, 2016.
   Paper [ML]
   
   

Graduated in 2019
Big Data Director, Intellifusion, China
URL: https://scholar.google.com.hk/citations?user=LHgchLkAAAAJ&hl=en
Email: xtyu@cse.cuhk.edu.hk

“Efficient Learning in Stochastic Bandits” Thesis Presentation

1. “Pure Exploration of Multi-Armed Bandits with Heavy-Tailed Payoffs,” Xiaotian Yu, Han Shao, Michael R. Lyu, Irwin King, in Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence (UAI2018), pp. 937-946, Monterey, USA, August 6 - August 10, 2018.
   Paper [ML]
   
   
2. “A Generic Approach for Accelerating Stochastic Zeroth-Order Convex Optimization,” Xiaotian Yu, Irwin King, Michael R. Lyu, Tianbao Yang, in Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI2018), pp. 3040-3046, Stockholm, Sweden, July 13 - July 19, 2018.
   Paper [ML]
   
   
3. “Risk Control of Best Arm Identification in Multi-Armed Bandits via Successive Rejects,” Xiaotian Yu, Irwin King, Michael R. Lyu, in Proceedings of the 17th IEEE International Conference on Data Mining (ICDM2017), pp. 1147-1152, New Orleans, USA, November 18 - November 21, 2017.
   Paper [ML]
   
   
4. “CBRAP: Contextual Bandits with RAndom Projection,” Xiaotian Yu, Michael R. Lyu, Irwin King, in Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI2017), pp. 2859-2866, San Francisco, USA, February 4 - February 9, 2017.
   Paper [ML]
   
   
5. “Online Non-Negative Dictionary Learning via Moment Information for Sparse Poisson Coding,” Xiaotian Yu, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2016 IEEE International Joint Conference on Neural Networks (IJCNN2016), pp. 5094-5101, Vancouver, Canada, July 24 - July 29, 2016.
   Paper [ML]
   
   

Graduated in 2018
Assistant Professor, Fudan University, China
URL: http://www.cse.cuhk.edu.hk/~hxu
Email: hxu@cse.cuhk.edu.hk

“Software Obfuscation with Layered Security” Thesis Presentation

1. “Layered Obfuscation: A Taxonomy of Software Obfuscation Techniques for Layered Security,” Hui Xu, Yangfan Zhou, Jiang Ming, Michael R. Lyu, Cybersecurity (CYBERSECURITY), vol. 3, no. 9, pp. 1-18, 2020.
   Paper [SE]
   
   
2. “Benchmarking the Capability of Symbolic Execution Tools with Logic Bombs,” Hui Xu, Zirui Zhao, Yangfan Zhou, Michael R. Lyu, IEEE Transactions on Dependable and Secure Computing (TDSC), vol. 17, no. 6, pp. 1243-1256, 2020.
   Paper [SE]
   
   
3. “Assessing the Security Properties of Software Obfuscation,” Hui Xu, Michael R. Lyu, IEEE Security and Privacy (SECURPRIV), vol. 14, no. 5, pp. 80-83, 2016.
   Paper [SE]
   
   

1. “NV-DNN: Towards Fault-Tolerant DNN Systems with N-Version Programming,” Hui Xu, Zhuangbin Chen, Weibin Wu, Zhi Jin, Sy-Yen Kuo, Michael R. Lyu, in Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSNW2019), pp. 44-47, Portland, USA, June 24 - June 27, 2019.
   Paper [SE]
   
   
2. “Manufacturing Resilient Bi-Opaque Predicates Against Symbolic Execution,” Hui Xu, Yangfan Zhou, Yu Kang, Fengzhi Tu, Michael R. Lyu, in Proceedings of the 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2018), pp. 666-677, Luxembourg City, Luxembourg, June 25 - June 28, 2018.
   Paper [SE]
   
   
3. “Concolic Execution on Small-Size Binaries: Challenges and Empirical Study,” Hui Xu, Yangfan Zhou, Yu Kang, Michael R. Lyu, in Proceedings of the 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2017), pp. 181-188, Denver, USA, June 26 - June 29, 2017.
   Paper [SE]
   
   
4. “N-Version Obfuscation,” Hui Xu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 2nd ACM International Workshop on Cyber-Physical System Security (AsiaCCS:CPSS2016), pp. 22-33, Xi'an, China, May 30, 2016.
   Paper [SE]
   
   
5. “SpyAware: Investigating the Privacy Leakage Signatures in App Execution Traces,” Hui Xu, Yangfan Zhou, Cuiyun Gao, Yu Kang, Michael R. Lyu, in Proceedings of the 26th IEEE International Symposium on Software Reliability Engineering (ISSRE2015), pp. 348-358, Washington DC, USA, November 2 - November 5, 2015.
   Paper [SE]
   
   
6. “Towards Continuous and Passive Authentication via Touch Biometrics: An Experimental Study on Smartphones,” Hui Xu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 10th Symposium on Usable Privacy and Security (SOUPS2014), pp. 187-198, Menlo Park, USA, July 9 - July 11, 2014.
   Paper [SE]
   
   

Graduated in 2018
Assistant Professor, Harbin Institute of Technology (Shenzhen), China
URL: https://cuiyungao.github.io/
Email: cygao@cse.cuhk.edu.hk

“User Review Mining for Assisting App Development” Thesis Presentation

1. “Do Users Care about Ad's Performance Costs? Exploring the Effects of the Performance Costs of In-App Ads on User Experience,” Cuiyun Gao, Jichuan Zeng, Federica Sarro, David Lo, Irwin King, Michael R. Lyu, Information and Software Technology (IST), vol. 138, no. 106471, 2021.
   Paper [SE]
   
   

1. “Automating App Review Response Generation,” Cuiyun Gao, Jichuan Zeng, Xin Xia, David Lo, Michael R. Lyu, Irwin King, in Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering (ASE2019), pp. 163-175, San Diego, USA, November 11 - November 15, 2019.
   Paper [SE]
   
   
2. “Emerging App Issue Identification from User Feedback: Experience on WeChat,” Cuiyun Gao, Wujie Zheng, Yuetang Deng, David Lo, Jichuan Zeng, Michael R. Lyu, Irwin King, in Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE:SEIP2019), pp. 279-288, Montreal, Canada, May 25 - May 31, 2019.
   Paper [SE]
   
   
3. “INFAR: Insight Extraction From App Reviews,” Cuiyun Gao, Jichuan Zeng, David Lo, Chin-Yew Lin, Michael R. Lyu, Irwin King, in Proceedings of the 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2018), pp. 904-907, Lake Buena Vista, USA, November 4 - November 9, 2018.
   Paper [SE]
   
   
4. “Exploring the Effects of Ad Schemes on the Performance Cost of Mobile Phones,” Cuiyun Gao, Jichuan Zeng, Federica Sarro, Michael R. Lyu, Irwin King, in Proceedings of the 1st International Workshop on Advances in Mobile App Analysis (ASE:A-Mobile2018), pp. 13-18, Corum, Montpellier, France, September 4, 2018.
   Paper [SE]
   
   
5. “Online App Review Analysis for Identifying Emerging Issues,” Cuiyun Gao, Jichuan Zeng, Michael R. Lyu, Irwin King, in Proceedings of the 40th International Conference on Software Engineering (ICSE2018), pp. 48-58, Gothenburg, Sweden, May 27 - June 3, 2018.
   Paper [SE]
   
   
6. “IntelliAd: Assisting Mobile App Developers in Measuring Ad Costs Automatically,” Cuiyun Gao, Yichuan Man, Hui Xu, Jieming Zhu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 39th International Conference on Software Engineering Companion Volume (ICSE:C2017), pp. 253-255, Buenos Aires, Argentina, May 20 - May 28, 2017.
   Paper [SE]
   
   
7. “PAID: Prioritizing App Issues for Developers by Tracking User Reviews over Versions,” Cuiyun Gao, Baoxiang Wang, Pinjia He, Jieming Zhu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 26th IEEE International Symposium on Software Reliability Engineering (ISSRE2015), pp. 35-45, Washington DC, USA, November 2 - November 5, 2015.
   Paper [SE]
   
   

Graduated in 2018
Postdoctoral fellow, ETH Zurich, Switzerland
URL: https://pinjiahe.github.io/
Email: pjhe@cse.cuhk.edu.hk

“Automated Runtime Data Analysis for System Reliability Management” Thesis Presentation

1. “Towards Automated Log Parsing for Large-Scale Log Data Analysis,” Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu, IEEE Transactions on Dependable and Secure Computing (TDSC), vol. 15, no. 6, pp. 931-944, 2018.
   Paper [SE]
   
   

1. “Characterizing the Natural Language Descriptions in Software Logging Statements,” Pinjia He, Zhuangbin Chen, Shilin He, Michael R. Lyu, in Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering (ASE2018), pp. 178-189, Corum, Montpellier, France, September 3 - September 7, 2018.
   Paper [SE]
   
   
2. “Drain: An Online Log Parsing Approach with Fixed Depth Tree,” Pinjia He, Jieming Zhu, Zibin Zheng, Michael R. Lyu, in Proceedings of the 24th IEEE International Conference on Web Services (ICWS2017), pp. 33-40, Honolulu, USA, June 25 - June 30, 2017.
   Paper [DS]
   
   
3. “An Evaluation Study on Log Parsing and Its Use in Log Mining,” Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu, in Proceedings of the 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2016), pp. 654-661, Toulouse, France, June 28 - July 1, 2016.
   Paper [SE]
   
   
4. “Location-Based Hierarchical Matrix Factorization for Web Service Recommendation,” Pinjia He, Jieming Zhu, Zibin Zheng, Jianlong Xu, Michael R. Lyu, in Proceedings of the 21st IEEE International Conference on Web Services (ICWS2014), pp. 297-304, Anchorage, USA, June 27 - July 2, 2014.
   Paper [DS]
   
   
5. “A Hierarchical Matrix Factorization Approach for Location-Based Web Service QoS Prediction,” Pinjia He, Jieming Zhu, Jianlong Xu, Michael R. Lyu, in Proceedings of the 8th IEEE International Symposium on Service-Oriented System Engineering (SOSE2014), pp. 290-295, Oxford, The United Kingdom, April 7 - April 11, 2014.
   Paper [DS]
   
   

Graduated in 2018
Researcher, Tencent Cooperation, China
URL: https://scholar.google.com/citations?user=mUMrk7oAAAAJ&hl=en
Email: xxchen@cse.cuhk.edu.hk

“Randomized Algorithms for Machine Learning” Thesis Presentation

1. “Making Online Sketching Hashing Even Faster,” Xixian Chen, Haiqin Yang, Shenglin Zhao, Michael R. Lyu, Irwin King, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 33, no. 3, pp. 1089-1101, 2021.
   Paper [ML]
   
   
2. “Effective Data-Aware Covariance Estimator from Compressed Data,” Xixian Chen, Haiqin Yang, Shenglin Zhao, Michael R. Lyu, Irwin King, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 31, no. 7, pp. 2441-2454, 2020.
   Paper [ML]
   
   

1. “Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data,” Xixian Chen, Michael R. Lyu, Irwin King, in Proceedings of the 34th International Conference on Machine Learning (ICML2017), pp. 767-776, Sydney, Australia, August6 - August 11, 2017.
   Paper [ML]
   
   
2. “FROSH: FasteR Online Sketching Hashing,” Xixian Chen, Irwin King, Michael R. Lyu, in Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI2017), Sydney, Australia, August 11 - August 15, 2017.
   Paper [ML]
   
   
3. “Training-Efficient Feature Map for Shift-Invariant Kernels,” Xixian Chen, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI2015), pp. 3395-3401, Buenos Aires, Argentina, July 25 - July 31, 2015.
   Paper [ML]
   
   

Graduated in 2017
Researcher, Tencent Cooperation, China
URL: https://scholar.google.com/citations?user=ZebV4_oAAAAJ&hl=en
Email: slzhao@cse.cuhk.edu.hk

“Point-of-Interest Recommendation in Location-Based Social Networks” Thesis Presentation

1. “Aggregated Temporal Tensor Factorization Model for Point-of-Interest Recommendation,” Shenglin Zhao, Irwin King, Michael R. Lyu, Neural Processing Letters (NPLETT), vol. 47, no. 3, pp. 975-992, 2018.
   Paper [ML]
   
   
2. “Point-of-Interest Recommendation in Location-Based Social Networks,” Shenglin Zhao, Michael R. Lyu, Irwin King, in Springer Briefs in Computer Science, pp. 1-99, Published by Springer, 2018.
   Paper [ML]
   
   

1. “Personalized Sequential Check-in Prediction: Beyond Geographical and Temporal Contexts,” Shenglin Zhao, Xixian Chen, Irwin King, Michael R. Lyu, in Proceedings of the 2018 IEEE International Conference on Multimedia and Expo (ICME2018), pp. 1-6, San Diego, USA, July 23 - July 27, 2018.
   Paper [MM]
   
   
2. “Geo-Pairwise Ranking Matrix Factorization Model for Point-of-Interest Recommendation,” Shenglin Zhao, Irwin King, Michael R. Lyu, in Proceedings of the 24th International Conference on Neural Information Processing (ICONIP2017), pp. 368-377, Guangzhou, China, November 14 - November 18, 2017.
   Paper [ML]
   
   
3. “Mining Business Opportunities from Location-Based Social Networks,” Shenglin Zhao, Irwin King, Michael R. Lyu, Jia Zeng, Mingxuan Yuan, in Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2017), pp. 1037-1040, Tokyo, Japan, August 7 - August 11, 2017.
   Paper [ML]
   
   
4. “Geo-Teaser: Geo-Temporal Sequential Embedding Rank for Point-of-Interest Recommendation,” Shenglin Zhao, Tong Zhao, Irwin King, Michael R. Lyu, in Proceedings of the 26th International Conference on World Wide Web Companion (WWW:C2017), pp. 153-162, Perth, Australia, April 3 - April 7, 2017.
   Paper [DS]
   
   
5. “Aggregated Temporal Tensor Factorization Model for Point-of-Interest Recommendation,” Shenglin Zhao, Michael R. Lyu, Irwin King, in Proceedings of the 23rd International Conference on Neural Information Processing (ICONIP2016), pp. 450-458, Kyoto, Japan, October 16 - October 21, 2016.
   Paper [ML]
   
   
6. “STELLAR: Spatial-Temporal Latent Ranking for Successive Point-of-Interest Recommendation,” Shenglin Zhao, Tong Zhao, Haiqin Yang, Michael R. Lyu, Irwin King, in Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI2016), pp. 315-322, Phoenix, USA, February 12 - February 17, 2016.
   Paper [ML]
   
   
7. “Capturing Geographical Influence in POI Recommendations,” Shenglin Zhao, Irwin King, Michael R. Lyu, in Proceedings of the 20th International Conference on Neural Information Processing (ICONIP2013), pp. 530-537, Daegu, Korea, November 3 - November 7, 2013.
   Paper [ML]
   
   

Graduated in 2017
Researcher, Microsoft, Canada
URL: https://scholar.google.com/citations?user=J-RLFt0AAAAJ&hl=en
Email: hyzhang@cse.cuhk.edu.hk

“Modeling the Relationship between Links and Communities for Overlapping Community” Thesis Presentation

1. “Overlapping Community Detection with Preference and Locality Information: A Non-Negative Matrix Factorization Approach,” Hongyi Zhang, Xingyu Niu, Irwin King, Michael R. Lyu, Social Network Analysis and Mining (SNAM), vol. 8, no. 1, pp. 43:1-43:14, 2018.
   Paper [ML]
   
   

1. “Modeling the Homophily Effect between Links and Communities for Overlapping Community Detection,” Hongyi Zhang, Tong Zhao, Irwin King, Michael R. Lyu, in Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI2016), pp. 3938-3944, New York, USA, July 9 - July 15, 2016.
   Paper [ML]
   
   
2. “Exploiting k-Degree Locality to Improve Overlapping Community Detection,” Hongyi Zhang, Michael R. Lyu, Irwin King, in Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI2015), pp. 2394-2400, Buenos Aires, Argentina, July 25 - July 31, 2015.
   Paper [ML]
   
   
3. “Incorporating Implicit Link Preference Into Overlapping Community Detection,” Hongyi Zhang, Irwin King, Michael R. Lyu, in Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI2015), pp. 396-402, Austin, USA, January 25 - January 30, 2015.
   Paper [ML]
   
   

Graduated in 2016
Researcher, Microsoft Research Asia, China
URL: https://wiki.cse.cuhk.edu.hk/user/ykang/doku.php
Email: ykang@cse.cuhk.edu.hk

“Performance Diagnosis of Cloud-Based Mobile Applications” Thesis Presentation

1. “DiagDroid: Android Performance Diagnosis via Anatomizing Asynchronous Executions,” Yu Kang, Yangfan Zhou, Hui Xu, Michael R. Lyu, in Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE2016), pp. 410-421, Seattle, USA, November 13 - November 18, 2016.
   Paper [SE]
   
   
2. “Experience Report: Detecting Poor-Responsive UI in Android Applications,” Yu Kang, Yangfan Zhou, Min Gao, Yixia Sun, Michael R. Lyu, in Proceedings of the 27th IEEE International Symposium on Software Reliability Engineering (ISSRE2016), pp. 490-501, Ottawa, Canada, October 23 - October 27, 2016.
   Paper [SE]
   
   
3. “A Latency-Aware Co-Deployment Mechanism for Cloud-Based Services,” Yu Kang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 5th IEEE International Conference on Cloud Computing (CLOUD2012), pp. 630-637, Honolulu, USA, June 24 - June 29, 2012.
   Paper [DS]
   
   
4. “A User Experience-Based Cloud Service Redeployment Mechanism,” Yu Kang, Yangfan Zhou, Zibin Zheng, Michael R. Lyu, in Proceedings of the 4th IEEE International Conference on Cloud Computing (CLOUD2011), pp. 227-234, Washington DC, USA, July 4 - July 9, 2011.
   Paper [DS]
   
   

Graduated in 2016
Researcher, Huawei Noah's Ark Lab, China
URL: https://jiemingzhu.github.io/
Email: jmzhu@cse.cuhk.edu.hk

“Data-Driven Quality Management of Online Service Systems” Thesis Presentation

1. “Online QoS Prediction for Runtime Service Adaptation via Adaptive Matrix Factorization,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 28, no. 10, pp. 2911-2924, 2017.
   Paper [DS]
   
   

1. “Tools and Benchmarks for Automated Log Parsing,” Jieming Zhu, Shilin He, Jinyang Liu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu, in Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE:SEIP2019), pp. 121-130, Montreal, Canada, May 25 - May 31, 2019.
   Paper [SE]
   
   
2. “CARP: Context-Aware Reliability Prediction of Black-Box Web Services,” Jieming Zhu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu, in Proceedings of the 24th IEEE International Conference on Web Services (ICWS2017), pp. 17-24, Honolulu, USA, June 25 - June 30, 2017.
   Paper [DS]
   
   
3. “A Privacy-Preserving QoS Prediction Framework for Web Service Recommendation,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 22nd IEEE International Conference on Web Services (ICWS2015), pp. 241-248, New York, USA, June 27 - July 2, 2015.
   Paper [DS]
   
   
4. “Learning to Log: Helping Developers Make Informed Logging Decisions,” Jieming Zhu, Pinjia He, Qiang Fu, Hongyu Zhang, Michael R. Lyu, Dongmei Zhang, in Proceedings of the 37th IEEE/ACM International Conference on Software Engineering (ICSE2015), pp. 415-425, Florence, Italy, May 16 - May 24, 2015.
   Paper [SE]
   
   
5. “Towards Online, Accurate, and Scalable QoS Prediction for Runtime Service Adaptation,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 34th International Conference on Distributed Computing Systems Workshops (ICDCS2014), pp. 318-327, Madrid, Spain, June 30 - July 3, 2014.
   Paper [DS]
   
   
6. “DR2: Dynamic Request Routing for Tolerating Latency Variability in Online Cloud Applications,” Jieming Zhu, Zibin Zheng, Michael R. Lyu, in Proceedings of the 6th IEEE International Conference on Cloud Computing (CLOUD2013), pp. 589-596, Santa Clara, USA, June 28 - July 3, 2013.
   Paper [DS]
   
   
7. “Scaling Service-Oriented Applications into Geo-Distributed Clouds,” Jieming Zhu, Zibin Zheng, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 7th IEEE International Symposium on Service-Oriented System Engineering (SOSE2013), pp. 335-340, San Francisco, USA, March 25 - March 28, 2013.
   Paper [DS]
   
   
8. “WSP: A Network Coordinate Based Web Service Positioning Framework for Response Time Prediction,” Jieming Zhu, Yu Kang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 19th IEEE International Conference on Web Services (ICWS2012), pp. 90-97, Honolulu, USA, June 24 - June 29, 2012.
   Paper [DS]
   
   
9. “A Clustering-Based QoS Prediction Approach for Web Service Recommendation,” Jieming Zhu, Yu Kang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 15th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORCW2012), pp. 93-98, Shenzhen, China, April 11, 2012.
   Paper [DS]
   
   

Graduated in 2015
Researcher, Baidu Cooperation, China
URL: https://scholar.google.com.hk/citations?user=H-fYF2EAAAAJ&hl=en
Email: ccheng@cse.cuhk.edu.hk

“Recommendation Systems for Mobile Location Based Service” Thesis Presentation

1. “A Unified Point-of-Interest Recommendation Framework in Location-Based Social Networks,” Chen Cheng, Haiqin Yang, Irwin King, Michael R. Lyu, ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, no. 1, pp. 10:1-10:21, 2016.
   Paper [ML]
   
   

1. “Gradient Boosting Factorization Machines,” Chen Cheng, Fen Xia, Tong Zhang, Irwin King, Michael R. Lyu, in Proceedings of the 8th ACM Conference on Recommender Systems (RecSys2014), pp. 265-272, Foster City, USA, October 6 - October 10, 2014.
   Paper [ML]
   
   
2. “Where You Like to Go Next: Successive Point-of-Interest Recommendation,” Chen Cheng, Haiqin Yang, Michael R. Lyu, Irwin King, in Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI2013), pp. 2605-2611, Beijing, China, August 3 - August 9, 2013.
   Paper [ML]
   
   
3. “Fused Matrix Factorization with Geographical and Social Influence in Location-Based Social Networks,” Chen Cheng, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI2012), Toronto, Canada, July 22 - July 26, 2012.
   Paper [ML]
   
   

Graduated in 2015
Researcher, WeBank, China
URL: https://scholar.google.com.hk/citations?user=d_Y6BFMAAAAJ&hl=en
Email: gling@cse.cuhk.edu.hk

“Learning to Improve Recommender Systems” Thesis Presentation

1. “Ratings Meet Reviews, a Combined Approach to Recommend,” Guang Ling, Michael R. Lyu, Irwin King, in Proceedings of the 8th ACM Conference on Recommender Systems (RecSys2014), pp. 105-112, Foster City, USA, October 6 - October 10, 2014.
   Paper [ML]
   
   
2. “A Unified Framework for Reputation Estimation in Online Rating Systems,” Guang Ling, Irwin King, Michael R. Lyu, in Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI2013), pp. 2670-2676, Beijing, China, August 3 - August 9, 2013.
   Paper [ML]
   
   
3. “Response Aware Model-Based Collaborative Filtering,” Guang Ling, Haiqin Yang, Michael R. Lyu, Irwin King, in Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI2012), pp. 501-510, Catalina Island, USA, August 14 - August 18, 2012.
   Paper [ML]
   
   
4. “Online Learning for Collaborative Filtering,” Guang Ling, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2012 IEEE International Joint Conference on Neural Networks (IJCNN2012), pp. 1-8, Brisbane, Australia, June 10 - June 15, 2012.
   Paper [ML]
   
   

Graduated in 2014
Researcher, Amazon, USA
URL: http://www.chenshouyuan.com/
Email: chenshouyuan@gmail.com

“Learning with Limited Samples” Thesis Presentation

1. “Fast Relative-Error Approximation Algorithm for Ridge Regression,” Shouyuan Chen, Yang Liu, Michael R. Lyu, Irwin King, Shengyu Zhang, in Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI2015), pp. 201-210, Amsterdam, The Netherlands, July 12 - July 16, 2015.
   Paper [ML]
   
   
2. “Combinatorial Pure Exploration of Multi-Armed Bandits,” Shouyuan Chen, Tian Lin, Irwin King, Michael R. Lyu, Wei Chen, in Proceedings of the 28th Conference on Neural Information Processing Systems (NIPS2014), pp. 379-387, Montreal, Canada, December 8 - December 13, 2014.
   NIPS 2014 Oral Presentation
   Paper [ML]
   
   
3. “Exact and Stable Recovery of Pairwise Interaction Tensors,” Shouyuan Chen, Michael R. Lyu, Irwin King, Zenglin Xu, in Proceedings of the 27th Conference on Neural Information Processing Systems (NIPS2013), pp. 1691-1699, Lake Tahoe, USA, December 5 - December 8, 2013.
   Paper [ML]
   
   

Graduated in 2014
Researcher, Baidu Cooperation, China
URL: https://scholar.google.com.hk/citations?user=hr-9OS8AAAAJ&hl=en
Email: bcli@cse.cuhk.edu.hk

“A Computational Framework for Question Processing in Community Question Answering Services” Thesis Presentation

1. “A Topic-Biased User Reputation Model in Rating Systems,” Baichuan Li, Rong-Hua Li, Irwin King, Michael R. Lyu, Jeffrey Xu Yu, Knowledge and Information Systems (KAIS), vol. 44, no. 3, pp. 581-607, 2015.
   Paper [ML]
   
   

1. “A Hierarchical Entity-Based Approach to Structuralize User Generated Content in Social Media: A Case of Yahoo! Answers,” Baichuan Li, Jing Liu, Chin-Yew Lin, Irwin King, Michael R. Lyu, in Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP2013), pp. 1521-1532, Seattle, USA, October 18 - October 21, 2013.
   Paper [ML]
   
   
2. “Communities of Yahoo! Answers and Baidu Zhidao: Complementing or competing?,” Baichuan Li, Michael R. Lyu, Irwin King, in Proceedings of the 2012 IEEE International Joint Conference on Neural Networks (IJCNN2012), pp. 1-8, Brisbane, Australia, June 10 - June 15, 2012.
   Paper [ML]
   
   
3. “Analyzing and Predicting Question Quality in Community Question Answering Services,” Baichuan Li, Tan Jin, Michael R. Lyu, Irwin King, Barley Mak, in Proceedings of the 21st International Conference on World Wide Web Companion (WWW:C2012), pp. 775-782, Lyon, France, April 16 - April 20, 2012.
   Paper [DS]
   
   
4. “Question Routing in Community Question Answering: Putting Category in Its Place,” Baichuan Li, Irwin King, Michael R. Lyu, in Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM2011), pp. 2041-2044, Glasgow, United Kingdom, October 24 - October 28, 2011.
   Paper [ML]
   
   
5. “Question Identification on Twitter,” Baichuan Li, Xiance Si, Michael R. Lyu, Irwin King, Edward Y. Chang, in Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM2011), pp. 2477-2480, Glasgow, United Kingdom, October 24 - October 28, 2011.
   Paper [ML]
   
   

Graduated in 2013
Associate Professor, Anhui Normal University, China
URL: https://stonezyl.github.io
Email: stonezyl@gmail.com

“Modeling and Exploiting QoS Prediction in Cloud and Service Computing” Thesis Presentation

1. “QoS Prediction in Cloud and Service Computing: Approaches and Applications,” Yilei Zhang, Michael R. Lyu, in Springer Briefs in Computer Science, pp. 1-122, Published by Springer, 2017.
   Paper [DS]
   
   
2. “An Online Performance Prediction Framework for Service-Oriented Systems,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, IEEE Transactions on Systems, Man, and Cybernetics: Systems (TSMC), vol. 44, no. 9, pp. 1169-1181, 2014.
   Paper [ML]
   
   

1. “Real-Time Performance Prediction for Cloud Components,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 15th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORCW2012), pp. 106-111, Shenzhen, China, April 11, 2012.
   Paper [DS]
   
   
2. “WSPred: A Time-Aware Personalized QoS Prediction Framework for Web Services,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 22nd IEEE International Symposium on Software Reliability Engineering (ISSRE2011), pp. 210-219, Tokyo, Japan, November 29 - December 2, 2011.
   Paper [SE]
   
   
3. “Exploring Latent Features for Memory-Based QoS Prediction in Cloud Computing,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 30th Symposium on Reliable Distributed Systems (SRDS2011), pp. 1-10, Madrid, Spain, October 4 - October 7, 2011.
   Paper [DS]
   
   
4. “BFTCloud: A Byzantine Fault Tolerance Framework for Voluntary-Resource Cloud Computing,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 4th IEEE International Conference on Cloud Computing (CLOUD2011), pp. 444-451, Washington DC, USA, July 4 - July 9, 2011.
   Paper [DS]
   
   
5. “WSExpress: A QoS-Aware Search Engine for Web Services,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Web Services (ICWS2010), pp. 91-98, Miami, USA, July 5 - July 10, 2010.
   Paper [DS]
   
   

Graduated in 2013
Assistant Professor, Georgia Institute of Technology, USA
URL: http://helloqirun.github.io/
Email: qrzhang@gatech.edu

“Scaling CFL-Reachability-Based Alias Analysis: Theory and Practice” Thesis Presentation

1. “Fast Algorithms for Dyck-CFL-Reachability with Applications to Alias Analysis,” Qirun Zhang, Michael R. Lyu, Hao Yuan, Zhendong Su, in Proceedings of the 34th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI2013), pp. 435-446, Seattle, USA, June 16 - June 19, 2013.
   Paper [SE]
   
   
2. “Flow-Augmented Call Graph: A New Foundation for Taming API Complexity,” Qirun Zhang, Wujie Zheng, Michael R. Lyu, in Proceedings of the 14th International Conference on Fundamental Approaches to Software Engineering (FASE2011), pp. 386-400, Saarbrucken, Germany, March 26 - April 3, 2011.
   Paper [SE]
   
   

Graduated in 2012
Manager, Tencent Cooperation, China
URL: https://scholar.google.com/citations?user=U2WBVlkAAAAJ&hl=en
Email: chaozhou1986@gmail.com

“Learning with Social Media” Thesis Presentation

1. “Learning to Suggest Questions in Social Media,” Tom Chao Zhou, Michael R. Lyu, Irwin King, Jie Lou, Knowledge and Information Systems (KAIS), vol. 43, no. 2, pp. 389-416, 2015.
   Paper [ML]
   
   

1. “A Data-Driven Approach to Question Subjectivity Identification in Community Question Answering,” Tom Chao Zhou, Xiance Si, Edward Y. Chang, Irwin King, Michael R. Lyu, in Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI2012), Toronto, Canada, July 22 - July 26, 2012.
   Paper [ML]
   
   
2. “A Classification-Based Approach to Question Routing in Community Question Answering,” Tom Chao Zhou, Michael R. Lyu, Irwin King, in Proceedings of the 21st International Conference on World Wide Web Companion (WWW:C2012), pp. 783-790, Lyon, France, April 16 - April 20, 2012.
   Paper [DS]
   
   
3. “Learning to Suggest Questions in Online Forums,” Tom Chao Zhou, Chin-Yew Lin, Irwin King, Michael R. Lyu, Young-In Song, Yunbo Cao, in Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI2011), San Francisco, USA, August 7 - August 11, 2011.
   Paper [ML]
   
   
4. “UserRec: A User Recommendation Framework in Social Tagging Systems,” Tom Chao Zhou, Hao Ma, Michael R. Lyu, Irwin King, in Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI2010), Atlanta, USA, July 11 - July 15, 2010.
   Paper [ML]
   
   
5. “TagRec: Leveraging Tagging Wisdom for Recommendation,” Tom Chao Zhou, Hao Ma, Irwin King, Michael R. Lyu, in Proceedings of the 12th IEEE International Conference on Computational Science and Engineering (CSE2009), pp. 194-199, Vancouver, Canada, August 29 - August 31, 2009.
   Paper [ML]
   
   

Graduated in 2012
Researcher, BIRD Shanghai, China
URL: https://dl.acm.org/profile/81490676127
Email: jjxiong@cse.cuhk.edu.hk

“Protocol Design, Testing, and Diagnosis towards Dependable Wireless Sensor Networks” Thesis Presentation

1. “MDiag: Mobility-Assisted Diagnosis for Wireless Sensor Networks,” Junjie Xiong, Yangfan Zhou, Michael R. Lyu, Evan F. Y. Young, Journal of Network and Computer Applications (JNCA), vol. 36, no. 1, pp. 167-177, 2013.
   Paper [DS]
   
   
2. “A Reliable and Efficient MAC Protocol for Underwater Acoustic Sensor Networks,” Junjie Xiong, Michael R. Lyu, Kam-Wing Ng, International Journal of Distributed Sensor Networks (IJDSN), vol. 7, no. 1, pp. 1-12, 2011.
   Paper [DS]
   
   

1. “Congestion Performance Improvement in Wireless Sensor Networks,” Junjie Xiong, Michael R. Lyu, Kam-Wing Ng, in Proceedings of the 2012 IEEE Aerospace Conference (Aerospace2012), pp. 1-9, Big Sky, Montana, USA, March 3 - March 10, 2012.
   Paper [DS]
   
   
2. “RealProct: Reliable Protocol Conformance Testing with Real Nodes for Wireless Sensor Networks,” Junjie Xiong, Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, in Proceedings of the IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom2011), pp. 572-581, Changsha, China, November 16 - November 18, 2011.
   Paper [DS]
   
   
3. “Mitigate the Bottleneck of Underwater Acoustic Sensor Networks via Priority Scheduling,” Junjie Xiong, Michael R. Lyu, Kam-Wing Ng, in Proceedings of the 6th International Conference on Mobile Ad-hoc and Sensor Networks (MSN2010), pp. 53-60, Hangzhou, China, December 20 - December 22, 2010.
   Paper [DS]
   
   

Graduated in 2011
Assistant Professor, Beijing Institute of Technology, China
URL: http://cs.bit.edu.cn/szdw/jsml/fjs/xx/index.htm
Email: xxin@bit.edu.cn

“Effective Fusion-Based Approaches for Recommender Systems” Thesis Presentation

1. “Do Ads Compete or Collaborate? Designing Click Models with Full Relationship Incorporated,” Xin Xin, Irwin King, Ritesh Agrawal, Michael R. Lyu, Heyan Huang, in Proceedings of the 21st ACM International Conference on Information and Knowledge Management (CIKM2012), pp. 1839-1843, Maui, USA, October 29 - November 2, 2012.
   Paper [ML]
   
   
2. “CMAP: Effective Fusion of Quality and Relevance for Multi-Criteria Recommendation,” Xin Xin, Michael R. Lyu, Irwin King, in Proceedings of the 4th ACM International Conference on Web Search and Data Mining (WSDM2011), pp. 455-464, Hong Kong, China, February 9 - February 12, 2011.
   Paper [ML]
   
   
3. “A Social Recommendation Framework Based on Multi-Scale Continuous Conditional Random Fields,” Xin Xin, Irwin King, Hongbo Deng, Michael R. Lyu, in Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM2009), pp. 1247-1256, Hong Kong, China, November 2 - November 6, 2009.
   Paper [ML]
   
   

Graduated in 2011
Researcher, Tencent Cooperation, China
URL: https://dl.acm.org/profile/81436593271
Email: wjzheng@cse.cuhk.edu.hk

“Automatic Software Testing Via Mining Software Data” Thesis Presentation

1. “Mining Test Oracles of Web Search Engines,” Wujie Zheng, Hao Ma, Michael R. Lyu, Tao Xie, Irwin King, in Proceedings of the 26th IEEE/ACM International Conference on Automated Software Engineering (ASE2011), pp. 408-411, Lawrence, USA, November 6 - November 10, 2011.
   Paper [SE]
   
   
2. “Cross-Library API Recommendation Using Web Search Engines,” Wujie Zheng, Qirun Zhang, Michael R. Lyu, in Proceedings of the 19th ACM SIGSOFT International Symposium on Foundations of Software Engineering and the 13th European Software Engineering Conference (ESEC/FSE2011), pp. 480-483, Szeged, Hungary, September 5 - September 9, 2011.
   Paper [SE]
   
   
3. “Random Unit-Test Generation with MUT-Aware Sequence Recommendation,” Wujie Zheng, Qirun Zhang, Michael R. Lyu, Tao Xie, in Proceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering (ASE2010), pp. 293-296, Antwerp, Belgium, September 20 - September 24, 2010.
   Paper [SE]
   
   
4. “Test Selection for Result Inspection via Mining Predicate Rules,” Wujie Zheng, Michael R. Lyu, Tao Xie, in Proceedings of the 31st International Conference on Software Engineering Companion Volume (ICSE:C2009), pp. 219-222, Vancouver, Canada, May 16 - May 24, 2009.
   Paper [SE]
   
   

Graduated in 2011
Business Analyst, CITINet Systems Ltd., China
URL: https://scholar.google.com.au/citations?user=s8I4jjEAAAAJ&hl=en
Email: zjlin@cse.cuhk.edu.hk

“Link-Based Similarity Measurement Techniques and Applications” Thesis Presentation

1. “MatchSim: A Novel Similarity Measure Based on Maximum Neighborhood Matching,” Zhenjiang Lin, Michael R. Lyu, Irwin King, Knowledge and Information Systems (KAIS), vol. 32, no. 1, pp. 141-166, 2012.
   Paper [ML]
   
   

1. “MatchSim: A Novel Neighbor-Based Similarity Measure with Maximum Neighborhood Matching,” Zhenjiang Lin, Michael R. Lyu, Irwin King, in Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM2009), pp. 1613-1616, Hong Kong, China, November 2 - November 6, 2009.
   Paper [ML]
   
   
2. “Extending Link-Based Algorithms for Similar Web Pages with Neighborhood Structure,” Zhenjiang Lin, Michael R. Lyu, Irwin King, in Proceedings of the 6th IEEE / WIC / ACM International Conference on Web Intelligence (WI2007), pp. 263-266, Silicon Valley, USA, November 2 - November 5, 2007.
   Paper [DS]
   
   
3. “PageSim: A Novel Link-Based Similarity Measure for the World Wide Web,” Zhenjiang Lin, Irwin King, Michael R. Lyu, in Proceedings of the 5th IEEE / WIC / ACM International Conference on Web Intelligence (WI2006), pp. 687-693, Hong Kong, China, December 18 - December 22, 2006.
   Paper [DS]
   
   
4. “PageSim: A Novel Link-Based Measure of Web Page Similarity,” Zhenjiang Lin, Michael R. Lyu, Irwin King, in Proceedings of the 15th International Conference on World Wide Web (WWW2006), pp. 1019-1020, Edinburgh, The United Kingdom, May 23 - May 26, 2006.
   Paper [DS]
   
   

Graduated in 2010
SAIL Lab Founder, Ping An Life Insurance Co. of China Ltd., China
URL: https://hqyang.github.io/
Email: hqyang@ieee.org

“Sparse Learning Under Regularization Framework” Thesis Presentation

1. “Budget Constrained Non-Monotonic Feature Selection,” Haiqin Yang, Zenglin Xu, Michael R. Lyu, Irwin King, Neural Networks (NEURNET), vol. 71, pp. 214-224, 2015.
   Paper [ML]
   
   
2. “Maximum Margin Semi-Supervised Learning with Irrelevant Data,” Haiqin Yang, Kaizhu Huang, Irwin King, Michael R. Lyu, Neural Networks (NEURNET), vol. 70, pp. 90-102, 2015.
   Paper [ML]
   
   
3. “Boosting Response Aware Model-Based Collaborative Filtering,” Haiqin Yang, Guang Ling, Yuxin Su, Michael R. Lyu, Irwin King, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 27, no. 8, pp. 2064-2077, 2015.
   Paper [ML]
   
   
4. “Efficient Online Learning for Multitask Feature Selection,” Haiqin Yang, Michael R. Lyu, Irwin King, ACM Transactions on Knowledge Discovery from Data (TKDD), vol. 7, no. 2, pp. 6:1-6:27, 2013.
   Paper [ML]
   
   
5. “Sparse Learning Under Regularization Framework: Theory and Applications,” Haiqin Yang, Irwin King, Michael R. Lyu, in , pp. 1-152, Published by LAP LAMBERT Academic Publishing, 2011.
   Paper [ML]
   
   
6. “Efficient Sparse Generalized Multiple Kernel Learning,” Haiqin Yang, Zenglin Xu, Jieping Ye, Irwin King, Michael R. Lyu, IEEE Transactions on Neural Networks (TNN), vol. 22, no. 3, pp. 433-446, 2011.
   Paper [ML]
   
   
7. “Localized Support Vector Regression for Time Series Prediction,” Haiqin Yang, Kaizhu Huang, Irwin King, Michael R. Lyu, Neurocomputing (NEUROCOMPUTING), vol. 72, no. 10-12, pp. 2659-2669, 2009.
   Paper [ML]
   
   

1. “Non-Monotonic Feature Selection for Regression,” Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Lyu, in Proceedings of the 21st International Conference on Neural Information Processing (ICONIP2014), pp. 44-51, Kuching, Malaysia, November 3 - November 6, 2014.
   Paper [ML]
   
   
2. “Online Imbalanced Learning with Kernels,” Haiqin Yang, Junjie Hu, Michael R. Lyu, Irwin King, in Proceedings of the 27th Conference on Neural Information Processing Systems Workshop on Big Learning: Advances in Algorithms and Data Management (NIPS:Big Learning2013), pp. 5-10, Lake Tahoe, USA, December 5 - December 8, 2013.
   Paper [ML]
   
   
3. “Can Irrelevant Data Help Semi-Supervised Learning, Why and How?,” Haiqin Yang, Shenghuo Zhu, Irwin King, Michael R. Lyu, in Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM2011), pp. 937-946, Glasgow, United Kingdom, October 24 - October 28, 2011.
   Paper [ML]
   
   
4. “Online Learning for Multi-Task Feature Selection,” Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 19th ACM Conference on Information and Knowledge Management (CIKM2010), pp. 1693-1696, Toronto, Canada, October 26 - October 30, 2010.
   Paper [ML]
   
   
5. “Multi-Task Learning for One-Class Classification,” Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2010 IEEE International Joint Conference on Neural Networks (IJCNN2010), pp. 1-8, Barcelona, Spain, July 18 - July 23, 2010.
   Paper [ML]
   
   
6. “Online Learning for Group Lasso,” Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Lyu, in Proceedings of the 27th International Conference on Machine Learning (ICML2010), pp. 1191-1198, Haifa, Israel, June 21 - June 24, 2010.
   Paper [ML]
   
   
7. “Efficient Minimax Clustering Probability Machine by Generalized Probability Product Kernel,” Haiqin Yang, Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the 2008 IEEE International Joint Conference on Neural Networks (IJCNN2008), pp. 4014-4019, Hong Kong, China, June 1 - June 6, 2008.
   Paper [ML]
   
   
8. “Outliers Treatment in Support Vector Regression for Financial Time Series Prediction,” Haiqin Yang, Kaizhu Huang, Laiwan Chan, Irwin King, Michael R. Lyu, in Proceedings of the 11th International Conference on Neural Information Processing (ICONIP2004), pp. 1260-1265, Calcutta, India, November 22 - November 25, 2004.
   Paper [ML]
   
   

Graduated in 2010
Professor, Sun Yat-sen University, China
URL: http://www.zibinzheng.com/
Email: zibinzheng2@yeah.net

“QoS Management of Web Services” Thesis Presentation

1. “Service Fault Tolerance for Highly Reliable Service-Oriented Systems: An Overview,” Zibin Zheng, Michael R. Lyu, Huaimin Wang, Science China Information Sciences (SCIS), vol. 58, no. 5, pp. 1-12, 2015.
   Paper [DS]
   
   
2. “Selecting an Optimal Fault Tolerance Strategy for Reliable Service-Oriented Systems with Local and Global Constraints,” Zibin Zheng, Michael R. Lyu, IEEE Transactions on Computers (TC), vol. 64, no. 1, pp. 219-232, 2015.
   Paper [DS]
   
   
3. “Investigating QoS of Real-World Web Services,” Zibin Zheng, Yilei Zhang, Michael R. Lyu, IEEE Transactions on Services Computing (TSC), vol. 7, no. 1, pp. 32-39, 2014.
   Paper [DS]
   
   
4. “QoS Management of Web Services,” Zibin Zheng, Michael R. Lyu, in Advanced Topics in Science and Technology in China, pp. 1-162, Published by Springer, 2013.
   Paper [DS]
   
   
5. “Personalized Reliability Prediction of Web Services,” Zibin Zheng, Michael R. Lyu, ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 22, no. 2, pp. 12:1-12:25, 2013.
   Paper [SE]
   
   
6. “QoS Ranking Prediction for Cloud Services,” Zibin Zheng, Xinmiao Wu, Yilei Zhang, Michael R. Lyu, Jianmin Wang, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 24, no. 6, pp. 1213-1222, 2013.
   Paper [DS]
   
   
7. “Collaborative Web Service QoS Prediction via Neighborhood Integrated Matrix Factorization,” Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King, IEEE Transactions on Services Computing (TSC), vol. 6, no. 3, pp. 289-299, 2013.
   Paper [DS]
   
   
8. “Component Ranking for Fault-Tolerant Cloud Applications,” Zibin Zheng, Tom Chao Zhou, Michael R. Lyu, Irwin King, IEEE Transactions on Services Computing (TSC), vol. 5, no. 4, pp. 540-550, 2012.
   Paper [DS]
   
   
9. “QoS-Aware Web Service Recommendation by Collaborative Filtering,” Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King, IEEE Transactions on Services Computing (TSC), vol. 4, no. 2, pp. 140-152, 2011.
   Paper [DS]
   
   
10. “An Adaptive QoS-Aware Fault Tolerance Strategy for Web Services,” Zibin Zheng, Michael R. Lyu, Empirical Software Engineering (EMSE), vol. 15, no. 4, pp. 323-345, 2010.
    Paper [SE]
    
    
11. “Optimal Fault Tolerance Strategy Selection for Web Services,” Zibin Zheng, Michael R. Lyu, International Journal of Web Services Research (IJWSR), vol. 7, no. 4, pp. 21-40, 2010.
    Paper [DS]
    
    

1. “Service-Generated Big Data and Big Data-as-a-Service: An Overview,” Zibin Zheng, Jieming Zhu, Michael R. Lyu, in Proceedings of the 2013 IEEE International Congress on Big Data (BigData Congress2013), pp. 403-410, Santa Clara, USA, June 27 - July 2, 2013.
   Paper [ML]
   
   
2. “FTCloud: A Component Ranking Framework for Fault-Tolerant Cloud Applications,” Zibin Zheng, Tom Chao Zhou, Michael R. Lyu, Irwin King, in Proceedings of the 21st IEEE International Symposium on Software Reliability Engineering (ISSRE2010), pp. 398-407, San Jose, USA, November 1 - November 4, 2010.
   Paper [SE]
   
   
3. “CloudRank: A QoS-Driven Component Ranking Framework for Cloud Computing,” Zibin Zheng, Yilei Zhang, Michael R. Lyu, in Proceedings of the 29th Symposium on Reliable Distributed Systems (SRDS2010), pp. 184-193, New Delhi, India, October 31 - November 3, 2010.
   Paper [DS]
   
   
4. “Distributed QoS Evaluation for Real-World Web Services,” Zibin Zheng, Yilei Zhang, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Web Services (ICWS2010), pp. 83-90, Miami, USA, July 5 - July 10, 2010.
   ICWS 2010 Best Student Paper Award
   Paper [DS]
   
   
5. “A Collaborative Quality Ranking Framework for Cloud Components,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 40th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2010), Illinois, USA, June 28 - July 1, 2010.
   Paper [SE]
   
   
6. “Collaborative Reliability Prediction of Service-Oriented Systems,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering (ICSE2010), pp. 35-44, Cape Town, South Africa, May 1 - May 8, 2010.
   ACM SIGSOFT Distinguished Paper Award
   Paper [SE]
   
   
7. “Component Recommendation for Cloud Applications,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering: The 2nd International Workshop on Recommendation Systems for Software Engineering (ICSE:RSSE2010), pp. 48-49, Cape Town, South Africa, May 4, 2010.
   Paper [SE]
   
   
8. “WSRec: A Collaborative Filtering Based Web Service Recommender System,” Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King, in Proceedings of the 7th IEEE International Conference on Web Services (ICWS2009), pp. 437-444, Los Angeles, USA, July 6 - July 10, 2009.
   Best Paper Award Nomination, Invited for Journal Publication
   Paper [DS]
   
   
9. “A QoS-Aware Fault Tolerant Middleware for Dependable Service Composition,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 39th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2009), pp. 239-248, Lisbon, Portugal, June 29 - July 2, 2009.
   Paper [SE]
   
   
10. “A Runtime Dependability Evaluation Framework for Fault Tolerant Web Services,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 39th IEEE/IFIP International Conference on Dependable Systems & Networks: the 1st Workshop on Proactive Failure Avoidance, Recovery and Maintenance (DSNW:PFARM2009), pp. 9-14, Lisbon, Portugal, June 29 - July 2, 2009.
    Paper [SE]
    
    
11. “A QoS-Aware Middleware for Fault Tolerant Web Services,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 19th IEEE International Symposium on Software Reliability Engineering (ISSRE2008), pp. 97-106, Seattle, USA, November 11 - November 14, 2008.
    Best Papers for Journal Publication
    Paper [SE]
    
    
12. “A Distributed Replication Strategy Evaluation and Selection Framework for Fault Tolerant Web Services,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 6th IEEE International Conference on Web Services (ICWS2008), pp. 145-152, Beijing, China, September 23 - September 26, 2008.
    Best Paper Award Nomination, Invited for Journal Publication
    Paper [DS]
    
    
13. “WS-DREAM: A Distributed Reliability Assessment Mechanism for Web Services,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 38th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2008), pp. 392-397, Anchorage, USA, June 24 - June 27, 2008.
    Paper [SE]
    
    

Graduated in 2009
Research Scientist Manager, Facebook AI, USA
URL: https://www.haoma.io/
Email: haoma@haoma.io

“Learning to Recommend” Thesis Presentation

1. “Social Recommendation in Dynamic Networks,” Hao Ma, Irwin King, Michael R. Lyu, in Encyclopedia of Social Network Analysis and Mining, pp. 2772-2778, Published by Springer, 2018.
   Paper [ML]
   
   
2. “Social Recommendation in Dynamic Networks,” Hao Ma, Irwin King, Michael R. Lyu, in Encyclopedia of Social Network Analysis and Mining, pp. 1923-1929, Published by Springer, 2014.
   Paper [ML]
   
   
3. “Mining Web Graphs for Recommendations,” Hao Ma, Irwin King, Michael R. Lyu, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 24, no. 6, pp. 1051-1064, 2012.
   Paper [ML]
   
   
4. “Learning to Recommend with Explicit and Implicit Social Relations,” Hao Ma, Irwin King, Michael R. Lyu, ACM Transactions on Intelligent Systems and Technology (TIST), vol. 2, no. 3, pp. 29:1-29:19, 2011.
   Paper [ML]
   
   
5. “Improving Recommender Systems by Incorporating Social Contextual Information,” Hao Ma, Tom Chao Zhou, Michael R. Lyu, Irwin King, ACM Transactions on Information Systems (TOIS), vol. 29, no. 2, pp. 9:1-9:23, 2011.
   Paper [ML]
   
   
6. “Bridging the Semantic Gap Between Image Contents and Tags,” Hao Ma, Jianke Zhu, Michael R. Lyu, Irwin King, IEEE Transactions on Multimedia (TMM), vol. 12, no. 5, pp. 462-473, 2010.
   Paper [MM]
   
   

1. “Probabilistic Factor Models for Web Site Recommendation,” Hao Ma, Chao Liu, Irwin King, Michael R. Lyu, in Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2011), pp. 265-274, Beijing, China, July 25 - July 29, 2011.
   Paper [ML]
   
   
2. “Recommender Systems with Social Regularization,” Hao Ma, Dengyong Zhou, Chao Liu, Michael R. Lyu, Irwin King, in Proceedings of the 4th ACM International Conference on Web Search and Data Mining (WSDM2011), pp. 287-296, Hong Kong, China, February 9 - February 12, 2011.
   Paper [ML]
   
   
3. “Diversifying Query Suggestion Results,” Hao Ma, Michael R. Lyu, Irwin King, in Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI2010), Atlanta, USA, July 11 - July 15, 2010.
   Paper [ML]
   
   
4. “Semi-Nonnegative Matrix Factorization with Global Statistical Consistency for Collaborative Filtering,” Hao Ma, Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM2009), pp. 767-776, Hong Kong, China, November 2 - November 6, 2009.
   Paper [ML]
   
   
5. “Learning to Recommend with Trust and Distrust Relationships,” Hao Ma, Michael R. Lyu, Irwin King, in Proceedings of the 3rd ACM Conference on Recommender Systems (RecSys2009), pp. 189-196, New York, USA, October 23 - October 25, 2009.
   Paper [ML]
   
   
6. “Learning to Recommend with Social Trust Ensemble,” Hao Ma, Irwin King, Michael R. Lyu, in Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2009), pp. 203-210, Boston, USA, July 19 - July 23, 2009.
   SIGIR 2020 Test of Time Award
   Paper [ML]
   
   
7. “SoRec: Social Recommendation Using Probabilistic Matrix Factorization,” Hao Ma, Haixuan Yang, Michael R. Lyu, Irwin King, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 931-940, Napa Valley, USA, October 26 - October 30, 2008.
   CIKM 2019 Test of Time Award
   Paper [ML]
   
   
8. “Mining Social Networks Using Heat Diffusion Processes for Marketing Candidates Selection,” Hao Ma, Haixuan Yang, Michael R. Lyu, Irwin King, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 233-242, Napa Valley, USA, October 26 - October 30, 2008.
   Paper [ML]
   
   
9. “Learning Latent Semantic Relations from Clickthrough Data for Query Suggestion,” Hao Ma, Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 709-718, Napa Valley, USA, October 26 - October 30, 2008.
   Paper [ML]
   
   
10. “Effective Missing Data Prediction for Collaborative Filtering,” Hao Ma, Irwin King, Michael R. Lyu, in Proceedings of the 30th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2007), pp. 39-46, Amsterdam, The Netherlands, July 23 - July 27, 2007.
    Paper [ML]
    
    

Graduated in 2009
Associate Professor, Fudan University, China
URL: http://www.cs.fudan.edu.cn/en/?page_id=7307
Email: zyf@fudan.edu.cn

“Coverage-Oriented Network Scheduling and Location-Directed Data Collection: Towards Energy-Efficient Wireless Sensor Networks” Thesis Presentation

1. “On Sensor Network Reconfiguration for Downtime-Free System Migration,” Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, Mobile Networks and Applications (MNA), vol. 14, no. 2, pp. 241-252, 2009.
   Paper [DS]
   
   

1. “Online Protocol Verification in Wireless Sensor Networks via Non-Intrusive Behavior Profiling,” Yangfan Zhou, Xinyu Chen, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 7th International Conference on Wireless Algorithms, Systems, and Applications (WASA2012), pp. 100-111, Yellow Mountains, China, August 8 - August 10, 2012.
   Paper [DS]
   
   
2. “Sentomist: Unveiling Transient Sensor Network Bugs via Symptom Mining,” Yangfan Zhou, Xinyu Chen, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 30th International Conference on Distributed Computing Systems Workshops (ICDCS2010), pp. 784-794, Genova, Italy, June 21 - June 25, 2010.
   Paper [DS]
   
   
3. “Surviving Holes and Barriers in Geographic Data Reporting for Wireless Sensor Networks,” Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the IEEE 6th International Conference on Mobile Adhoc and Sensor Systems (MASS2009), pp. 50-59, Macao, China, October 12 - October 15, 2009.
   Paper [DS]
   
   
4. “Energy-Efficient On-Demand Active Contour Service for Sensor Networks,” Yangfan Zhou, Junjie Xiong, Michael R. Lyu, Jiangchuan Liu, Kam-Wing Ng, in Proceedings of the IEEE 6th International Conference on Mobile Adhoc and Sensor Systems (MASS2009), pp. 383-392, Macao, China, October 12 - October 15, 2009.
   Paper [DS]
   
   
5. “On Sensor Network Reconfiguration for Downtime-Free System Migrations,” Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 5th International ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QSHINE2008), Hong Kong, China, July 28 - July 31, 2008.
   Paper [DS]
   
   
6. “An Index-Based Sensor-Grouping Mechanism for Efficient Field-Coverage Wireless Sensor Networks,” Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2008 IEEE International Conference on Communications (ICC2008), pp. 2409-2415, Beijing, China, May 19 - May 23, 2008.
   Paper [DS]
   
   
7. “An Energy-Efficient Mechanism for Self-Monitoring Sensor Web,” Yangfan Zhou, Michael R. Lyu, in Proceedings of the 2007 IEEE Aerospace Conference (Aerospace2007), pp. 1-8, Big Sky, Montana, USA, March 3 - March 10, 2007.
   Paper [DS]
   
   
8. “POWER-SPEED: A Power-Controlled Real-Time Data Transport Protocol for Wireless Sensor-Actuator Networks,” Yangfan Zhou, Edith C. H. Ngai, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2007 IEEE Wireless Communications and Networking Conference (WCNC2007), pp. 3736-3740, Hong Kong, China, March 11 - March 15, 2007.
   Paper [DS]
   
   
9. “A Point-Distribution Index and Its Application to Sensor-Grouping in Wireless Sensor Networks,” Yangfan Zhou, Haixuan Yang, Michael R. Lyu, Edith C. H. Ngai, in Proceedings of the 2nd International Conference on Wireless Communications and Mobile Computing (IWCMC2006), pp. 1171-1176, Vancouver, Canada, July 3 - July 6, 2006.
   Paper [DS]
   
   
10. “PORT: A Price-Oriented Reliable Transport Protocol for Wireless Sensor Networks,” Yangfan Zhou, Michael R. Lyu, in Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering (ISSRE2005), pp. 117-126, Chicago, USA, November 8 - November 11, 2005.
    Paper [SE]
    
    
11. “On Setting up Energy-Efficient Paths with Transmitter Power Control in Wireless Sensor Networks,” Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the IEEE 2nd International Conference on Mobile Adhoc and Sensor Systems (MASS2005), Washington DC, USA, November 7 - November 10, 2005.
    Paper [DS]
    
    

Graduated in 2009
Senior Staff Engineer and Director, Alibaba, China
URL: https://sites.google.com/view/hongbodeng/
Email: arcatdeng@gmail.com

“Web Mining Techniques for Query Log Analysis and Expertise Retrieval” Thesis Presentation

1. “Enhanced Models for Expertise Retrieval Using Community-Aware Strategies,” Hongbo Deng, Irwin King, Michael R. Lyu, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 42, no. 1, pp. 93-106, 2012.
   Paper [ML]
   
   

1. “Modeling and Exploiting Heterogeneous Bibliographic Networks for Expertise Ranking,” Hongbo Deng, Jiawei Han, Michael R. Lyu, Irwin King, in Proceedings of the 12th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL2012), pp. 71-80, Washington DC, USA, June 10 - June 14, 2012.
   JCDL 2012 Vannevar Bush Best Paper Award
   Paper [DS]
   
   
2. “Enhancing Expertise Retrieval Using Community-Aware Strategies,” Hongbo Deng, Irwin King, Michael R. Lyu, in Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM2009), pp. 1733-1736, Hong Kong, China, November 2 - November 6, 2009.
   Paper [ML]
   
   
3. “Entropy-Biased Models for Query Representation on the Click Graph,” Hongbo Deng, Irwin King, Michael R. Lyu, in Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2009), pp. 339-346, Boston, USA, July 19 - July 23, 2009.
   Paper [ML]
   
   
4. “A Generalized Co-HITS Algorithm and Its Application to Bipartite Graphs,” Hongbo Deng, Michael R. Lyu, Irwin King, in Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2009), pp. 239-248, Paris, France, June 28 - July 1, 2009.
   Paper [ML]
   
   
5. “Effective Latent Space Graph-Based Re-Ranking Model with Global Consistency,” Hongbo Deng, Michael R. Lyu, Irwin King, in Proceedings of the 2nd ACM International Conference on Web Search and Data Mining (WSDM2009), pp. 212-221, Barcelona, Spain, February 9 - February 11, 2009.
   Paper [ML]
   
   
6. “Formal Models for Expert Finding on DBLP Bibliography Data,” Hongbo Deng, Irwin King, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Data Mining (ICDM2008), pp. 163-172, Pisa, Italy, December 15 - December 19, 2008.
   Paper [ML]
   
   
7. “Two-Stage Multi-Class AdaBoost for Facial Expression Recognition,” Hongbo Deng, Jianke Zhu, Michael R. Lyu, Irwin King, in Proceedings of the 2007 IEEE International Joint Conference on Neural Networks (IJCNN2007), pp. 3005-3010, Orlando, USA, August 12 - August 17, 2007.
   Paper [ML]
   
   

Graduated in 2009
Senior Associate, J.P. Morgan, China
URL: https://dl.acm.org/profile/81436599211
Email: xqli@cse.cuhk.edu.hk

“Achieving Secure and Cooperative Wireless Networks with Trust Modeling and Game Theory” Thesis Presentation

1. “A Coalitional Game Model for Heat Diffusion Based Incentive Routing and Forwarding Scheme,” Xiaoqi Li, Wujie Zheng, Michael R. Lyu, in Proceedings of the 8th International IFIP-TC 6 Networking Conference (NETWORKING2009), pp. 664-675, Aachen, Germany, May 11 - May 15, 2009.
   Paper [DS]
   
   
2. “A Novel Coalitional Game Model for Security Issues in Wireless Networks,” Xiaoqi Li, Michael R. Lyu, in Proceedings of the 2008 Global Communications Conference (GLOBECOM2008), pp. 1962-1967, New Orleans, USA, November 20 - December 4, 2008.
   Paper [DS]
   
   
3. “A Trust Model Based Routing Protocol for Secure Ad Hoc Networks,” Xiaoqi Li, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2004 IEEE Aerospace Conference (Aerospace2004), pp. 1286-1295, Big Sky, Montana, USA, March 6 - March 13, 2004.
   Paper [DS]
   
   

Graduated in 2008
Professor, Zhejiang University, China
URL: https://person.zju.edu.cn/en/jkzhu
Email: jkzhu@zju.edu.cn

“Deformable Surface Recovery and Its Applications” Thesis Presentation

1. “Near-Duplicate Keyframe Retrieval by Semi-Supervised Learning and Nonrigid Image Matching,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 7, no. 1, pp. 4:1-4:24, 2011.
   Paper [MM]
   
   
2. “A Fast 2D Shape Recovery Approach by Fusing Features and Appearance,” Jianke Zhu, Michael R. Lyu, Thomas S. Huang, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 31, no. 7, pp. 1210-1224, 2009.
   Paper [MM]
   
   
3. “Face Annotation Using Transductive Kernel Fisher Discriminant,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, IEEE Transactions on Multimedia (TMM), vol. 10, no. 1, pp. 86-96, 2008.
   Paper [MM]
   
   
4. “Robust Regularized Kernel Regression,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 38, no. 6, pp. 1639-1644, 2008.
   Paper [ML]
   
   

1. “Nonrigid Shape Recovery by Gaussian Process Regression,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2009), pp. 1319-1326, Miami, USA, June 20 - June 25, 2009.
   Paper [MM]
   
   
2. “Near-Duplicate Keyframe Retrieval by Nonrigid Image Matching,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan, in Proceedings of the 16th International Conference on Multimedia (ACMMM2008), pp. 41-50, Vancouver, Canada, October 26 - October 31, 2008.
   Paper [MM]
   
   
3. “An Effective Approach to 3D Deformable Surface Tracking,” Jianke Zhu, Steven C. H. Hoi, Zenglin Xu, Michael R. Lyu, in Proceedings of the 10th European Conference on Computer Vision (ECCV2008), pp. 766-779, Marseille, France, October 12 - October 18, 2008.
   Paper [MM]
   
   
4. “A Multi-Scale Tikhonov Regularization Scheme for Implicit Surface Modelling,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2007), Minneapolis, USA, June 18 - June 23, 2007.
   Paper [MM]
   
   
5. “Progressive Finite Newton Approach to Real-time Nonrigid Surface Detection,” Jianke Zhu, Michael R. Lyu, in Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2007), Minneapolis, USA, June 18 - June 23, 2007.
   Paper [MM]
   
   
6. “Real-Time Non-Rigid Shape Recovery Via Active Appearance Models for Augmented Reality,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 9th European Conference on Computer Vision (ECCV2006), pp. 186-197, Graz, Austria, May 7 - May 13, 2006.
   Paper [MM]
   
   
7. “Automatic 3D Face Modeling Using 2D Active Appearance Models,” Jianke Zhu, Steven C. H. Hoi, Edward H. H. Yau, Michael R. Lyu, in Proceedings of the 13th Pacific Conference on Computer Graphics and Applications (PG2005), pp. 1-3, Macao, China, October 12 - October 14, 2005.
   Paper [MM]
   
   

Graduated in 2008
Professor, Harbin Institute of Technology (Shenzhen), China
URL: http://cs.hitsz.edu.cn/info/1021/2300.htm
Email: xuzenglin@hit.edu.cn

“Learning from Unlabeled Data” Thesis Presentation

1. “More Than Semi-Supervised Learning: A Unified View on Learning with Labeled and Unlabeled Data,” Zenglin Xu, Irwin King, Michael R. Lyu, in , pp. 1-132, Published by LAP LAMBERT Academic Publishing, 2010.
   Paper [ML]
   
   
2. “Discriminative Semi-Supervised Feature Selection via Manifold Regularization,” Zenglin Xu, Irwin King, Michael R. Lyu, Rong Jin, IEEE Transactions on Neural Networks (TNN), vol. 21, no. 7, pp. 1033-1047, 2010.
   Paper [ML]
   
   
3. “A Novel Kernel-Based Maximum a Posteriori Classification Method,” Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu, Neural Networks (NEURNET), vol. 22, no. 7, pp. 977-987, 2009.
   Paper [ML]
   
   
4. “Feature Selection Based on Minimum Error Minimax Probability Machine,” Zenglin Xu, Irwin King, Michael R. Lyu, International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), vol. 21, no. 8, pp. 1279-1292, 2007.
   Paper [ML]
   
   

1. “Smooth Optimization for Effective Multiple Kernel Learning,” Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu, Irwin King, in Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI2010), Atlanta, USA, July 11 - July 15, 2010.
   Paper [ML]
   
   
2. “Simple and Efficient Multiple Kernel Learning by Group Lasso,” Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 27th International Conference on Machine Learning (ICML2010), pp. 1175-1182, Haifa, Israel, June 21 - June 24, 2010.
   Paper [ML]
   
   
3. “Adaptive Regularization for Transductive Support Vector Machine,” Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael R. Lyu, Zhirong Yang, in Proceedings of the 23rd Conference on Neural Information Processing Systems (NIPS2009), pp. 2125-2133, Vancouver, Canada, December 7 - December 10, 2009.
   Paper [ML]
   
   
4. “Discriminative Semi-Supervised Feature Selection via Manifold Regularization,” Zenglin Xu, Rong Jin, Michael R. Lyu, Irwin King, in Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI2009), pp. 1303-1308, Pasadena, USA, July 11 - July 17, 2009.
   Paper [ML]
   
   
5. “Non-Monotonic Feature Selection,” Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, Irwin King, in Proceedings of the 26th International Conference on Machine Learning (ICML2009), pp. 1145-1152, Montreal, Canada, June 14 - June 18, 2009.
   Paper [ML]
   
   
6. “An Extended Level Method for Efficient Multiple Kernel Learning,” Zenglin Xu, Rong Jin, Irwin King, Michael R. Lyu, in Proceedings of the 22nd Conference on Neural Information Processing Systems (NIPS2008), pp. 1825-1832, Vancouver, Canada, December 8 - December 11, 2008.
   Paper [ML]
   
   
7. “Semi-Supervised Text Categorization by Active Search,” Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu, Irwin King, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 1517-1518, Napa Valley, USA, October 26 - October 30, 2008.
   Paper [ML]
   
   
8. “Efficient Convex Relaxation for Transductive Support Vector Machine,” Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael R. Lyu, in Proceedings of the 21st Conference on Neural Information Processing Systems (NIPS2007), pp. 1641-1648, Vancouver, Canada, December 3 - December 6, 2007.
   Paper [ML]
   
   
9. “Kernel Maximum a Posteriori Classification with Error Bound Analysis,” Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu, in Proceedings of the 14th International Conference on Neural Information Processing (ICONIP2007), pp. 841-850, Kitakyushu, Japan, November 13 - November 16, 2007.
   Paper [ML]
   
   
10. “Maximum Margin Based Semi-Supervised Spectral Kernel Learning,” Zenglin Xu, Jianke Zhu, Michael R. Lyu, Irwin King, in Proceedings of the 2007 IEEE International Joint Conference on Neural Networks (IJCNN2007), pp. 418-423, Orlando, USA, August 12 - August 17, 2007.
    Paper [ML]
    
    
11. “Web Page Classification with Heterogeneous Data Fusion,” Zenglin Xu, Irwin King, Michael R. Lyu, in Proceedings of the 16th International Conference on World Wide Web (WWW2007), pp. 1171-1172, Banff, Canada, May 8 - May 12, 2007.
    Paper [DS]
    
    

Graduated in 2008
Lecturer, Hong Kong Community College, The Hong Kong Polytechnic University
URL: https://www.hkcc-polyu.edu.hk/en/about-hkcc/staff-directory/division-of-science-engineering-and-health-studies/index.php?sid=198
Email: pat.chan@cpce-polyu.edu.hk

“Building Reliable Web Services: Methodology, Composition, Modeling and Experiment” Thesis Presentation

1. “A Novel Scheme for Hybrid Digital Video Watermarking: Approach, Evaluation and Experimentation,” Pat Pik-Wah Chan, Michael R. Lyu, Roland T. Chin, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 15, no. 12, pp. 1638-1649, 2005.
   Paper [MM]
   
   

1. “Developing Aerospace Applications with a ReliableWeb Services Paradigm,” Pat Pik-Wah Chan, Michael R. Lyu, in Proceedings of the 2008 IEEE Aerospace Conference (Aerospace2008), pp. 1-13, Big Sky, Montana, USA, March 1 - March 8, 2008.
   Paper [DS]
   
   
2. “Dynamic Web Service Composition: A New Approach in Building Reliable Web Service,” Pat Pik-Wah Chan, Michael R. Lyu, in Proceedings of the 22nd International Conference on Advanced Information Networking and Applications (AINA2008), pp. 20-25, Ginowan, Japan, March 25 - March 28, 2008.
   Paper [DS]
   
   
3. “Reliable Web Services: Methodology, Experiment and Modeling,” Pat Pik-Wah Chan, Michael R. Lyu, Miroslaw Malek, in Proceedings of the 5th IEEE International Conference on Web Services (ICWS2007), pp. 679-686, Salt Lake City, USA, July 9 - July 13, 2007.
   Paper [DS]
   
   
4. “Making Services Fault Tolerant,” Pat Pik-Wah Chan, Michael R. Lyu, Miroslaw Malek, in Proceedings of the 3rd International Service Availability Symposium (ISAS2006), pp. 43-61, Helsinki, Finland, May 15 - May 16, 2006.
   Paper [DS]
   
   
5. “Digital Video Watermarking with a Genetic Algorithm,” Pat Pik-Wah Chan, Michael R. Lyu, in Proceedings of the 2005 International Conference on Digital Archive Technologies (ICDAT2005), pp. 139-153, Taipei, Taiwan, June 16 - June 17, 205.
   Paper [DS]
   
   
6. “Copyright Protection on the Web: A Hybrid Digital Video Watermarking Scheme,” Pat Pik-Wah Chan, Michael R. Lyu, Roland T. Chin, in Proceedings of the 13th international conference on World Wide Web: Alternate Track Papers & Posters (WWW:ATPP2004), pp. 354-355, New York, USA, May 17 - May 20, 2004.
   Paper [DS]
   
   
7. “A DWT-Based Digital Video Watermarking Scheme with Error Correcting Code,” Pat Pik-Wah Chan, Michael R. Lyu, in Proceedings of the 5th International Conference on Information and Communications Security (ICICS2003), pp. 202-213, Huhehaote, China, October 10 - October 13, 2003.
   Paper [DS]
   
   

Graduated in 2007
Associate Professor, Hong Kong University, China
URL: https://www.eee.hku.hk/~chngai/
Email: chngai@eee.hku.hk

“Delay-Oriented Reliable Communication and Coordination in Wireless Sensor-Actuator Networks” Thesis Presentation

1. “A Delay-Aware Reliable Event Reporting Framework for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, Ad Hoc Networks (ANET), vol. 8, no. 7, pp. 694-707, 2010.
   Paper [DS]
   
   
2. “An Adaptive Delay-Minimized Route Design for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Jiangchuan Liu, Michael R. Lyu, IEEE Transactions on Vehicular Technology (TVT), vol. 58, no. 9, pp. 5083-5094, 2009.
   Paper [DS]
   
   
3. “An Efficient Intruder Detection Algorithm Against Sinkhole Attacks in Wireless Sensor Networks,” Edith C. H. Ngai, Jiangchuan Liu, Michael R. Lyu, Computer Communications (COMPCOMM), vol. 30, no. 11-12, pp. 2353-2364, 2007.
   Paper [DS]
   
   

1. “LOFT: A Latency-Oriented Fault Tolerant Transport Protocol for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2007 Global Communications Conference (GLOBECOM2007), pp. 1318-1323, Washington DC, USA, November 26 - November 30, 2007.
   Paper [DS]
   
   
2. “An Adaptive Delay-Minimized Route Design for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Jiangchuan Liu, Michael R. Lyu, in Proceedings of the IEEE 4th International Conference on Mobile Adhoc and Sensor Systems (MASS2007), pp. 1-9, Pisa, Italy, October 8 - October 11, 2007.
   Paper [DS]
   
   
3. “Delay-Minimized Route Design for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Jiangchuan Liu, Michael R. Lyu, in Proceedings of the 2007 IEEE Wireless Communications and Networking Conference (WCNC2007), pp. 3675-3680, Hong Kong, China, March 11 - March 15, 2007.
   Paper [DS]
   
   
4. “Reliable Reporting of Delay-Sensitive Events in Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the IEEE 3rd International Conference on Mobile Adhoc and Sensor Systems (MASS2006), pp. 101-108, Vancouver, Canada, October 9 - October 12, 2006.
   Paper [DS]
   
   
5. “On the Intruder Detection for Sinkhole Attack in Wireless Sensor Networks,” Edith C. H. Ngai, Jiangchuan Liu, Michael R. Lyu, in Proceedings of the 2006 IEEE International Conference on Communications (ICC2006), pp. 3383-3389, Istanbul, Turkey, June 11 - June 15, 2006.
   Paper [DS]
   
   
6. “An Authentication Service Based on Trust and Clustering in Wireless Ad Hoc Networks: Description and Security Evaluation,” Edith C. H. Ngai, Michael R. Lyu, in Proceedings of the 2006 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC2006), pp. 94-103, Taichung, Taiwan, June 5 - June 7, 2006.
   Paper [DS]
   
   
7. “A Real-Time Communication Framework for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2006 IEEE Aerospace Conference (Aerospace2006), pp. 1-9, Big Sky, Montana, USA, March 4 - March 11, 2006.
   Paper [DS]
   
   
8. “An Authentication Service Against Dishonest Users in Mobile Ad Hoc Networks,” Edith C. H. Ngai, Michael R. Lyu, Roland T. Chin, in Proceedings of the 2004 IEEE Aerospace Conference (Aerospace2004), pp. 1275-1285, Big Sky, Montana, USA, March 6 - March 13, 2004.
   Paper [DS]
   
   
9. “Trust- and Clustering-Based Authentication Services in Mobile Ad Hoc Networks,” Edith C. H. Ngai, Michael R. Lyu, in Proceedings of the 24th International Conference on Distributed Computing Systems Workshops (ICDCSW2004), pp. 582-587, Tokyo, Japan, March 23 - March 24, 2004.
   Paper [DS]
   
   
10. “XVIP: An XML-Based Video Information Processing System,” Edith C. H. Ngai, Pat Pik-Wah Chan, Edward H. H. Yau, Michael R. Lyu, in Proceedings of the 26th Annual International Computer Software and Applications Conference (COMPSAC2002), pp. 173-178, Oxford, The United Kingdom, August 26 - August 29, 2002.
    Paper [SE]
    
    

Graduated in 2007
Lecturer Above the Bar, National University of Ireland Galway, Ireland
URL: https://www.nuigalway.ie/our-research/people/mathematics-statistics-and-applied-mathematics/haixuanyang/
Email: hxyang@cse.cuhk.edu.hk

“Machine Learning Models on Random Graphs” Thesis Presentation

1. “A Volume-Based Heat-Diffusion Classifier,” Haixuan Yang, Michael R. Lyu, Irwin King, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 39, no. 2, pp. 417-430, 2009.
   Paper [ML]
   
   
2. “The Generalized Dependency Degree Between Attributes,” Haixuan Yang, Irwin King, Michael R. Lyu, Journal of the Association for Information Science and Technology (JASIST), vol. 58, no. 14, pp. 2280-2294, 2007.
   Paper [ML]
   
   

1. “Learning with Consistency between Inductive Functions and Kernels,” Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 22nd Conference on Neural Information Processing Systems (NIPS2008), pp. 1849-1856, Vancouver, Canada, December 8 - December 11, 2008.
   Paper [ML]
   
   
2. “DiffusionRank: A Possible Penicillin for Web Spamming,” Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 30th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2007), pp. 431-438, Amsterdam, The Netherlands, July 23 - July 27, 2007.
   Paper [ML]
   
   
3. “Predictive Random Graph Ranking on the Web,” Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2006 IEEE International Joint Conference on Neural Networks (IJCNN2006), pp. 1825-1832, Vancouver, Canada, July 16 - July 21, 2006.
   Paper [ML]
   
   
4. “NHDC and PHDC: Non-Propagating and Propagating Heat Diffusion Classifiers,” Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 12th International Conference on Neural Information Processing (ICONIP2005), pp. 394-399, Taipei, Taiwan, October 30 - November 2, 2005.
   Paper [ML]
   
   
5. “Predictive Ranking: A Novel Page Ranking Approach by Estimating the Web Structure,” Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 14th International Conference on World Wide Web: Special Interest Tracks and Posters (WWW:SITP2005), pp. 944-945, Chiba, Japan, May 10 - May 14, 2005.
   Paper [DS]
   
   

Graduated in 2006
Managing Director, Salesforce Research Asia, Singapore
URL: https://sites.google.com/view/stevenhoi/
Email: stevenhoi@gmail.com

“Statistical Machine Learning for Data Mining and Collaborative Multimedia Retrieval” Thesis Presentation

1. “Batch Mode Active Learning with Applications to Text Categorization and Image Retrieval,” Steven C. H. Hoi, Rong Jin, Michael R. Lyu, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 21, no. 9, pp. 1233-1248, 2009.
   Paper [ML]
   
   
2. “Semisupervised SVM Batch Mode Active Learning with Applications to Image Retrieval,” Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu, ACM Transactions on Information Systems (TOIS), vol. 27, no. 3, pp. 16:1-16:29, 2009.
   Paper [ML]
   
   
3. “A Multimodal and Multilevel Ranking Scheme for Large-Scale Video Retrieval,” Steven C. H. Hoi, Michael R. Lyu, IEEE Transactions on Multimedia (TMM), vol. 10, no. 4, pp. 607-619, 2008.
   Paper [MM]
   
   
4. “A Unified Log-Based Relevance Feedback Scheme for Image Retrieval,” Steven C. H. Hoi, Michael R. Lyu, Rong Jin, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 18, no. 4, pp. 509-524, 2006.
   Paper [ML]
   
   

1. “Semi-Supervised SVM Batch Mode Active Learning for Image Retrieval,” Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu, in Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2008), Anchorage, USA, June 24 - June 26, 2008.
   Paper [MM]
   
   
2. “Learning Nonparametric Kernel Matrices from Pairwise Constraints,” Steven C. H. Hoi, Rong Jin, Michael R. Lyu, in Proceedings of the 24th International Conference on Machine Learning (ICML2007), pp. 361-368, Corvalis, USA, June 20 - June 24, 2007.
   Paper [ML]
   
   
3. “A Multimodal and Multilevel Ranking Framework for Content-Based Video Retrieval,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2007), pp. 1225-1228, Honolulu, USA, April 15 - April 20, 2007.
   Paper [MM]
   
   
4. “Learning the Unified Kernel Machines for Classification,” Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang, in Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2006), pp. 187-196, Las Vegas, USA, August 24 - August 27, 2008.
   Paper [ML]
   
   
5. “Learning Distance Metrics with Contextual Constraints for Image Retrieval,” Steven C. H. Hoi, Wei Liu, Michael R. Lyu, Wei-Ying Ma, in Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2006), pp. 2072-2078, New York, USA, June 17 - June 22, 2006.
   Paper [MM]
   
   
6. “Batch Mode Active Learning and Its Application to Medical Image Classification,” Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu, in Proceedings of the 23rd International Conference on Machine Learning (ICML2006), pp. 417-424, Pittsburgh, USA, June 25 - June 29, 2006.
   Paper [ML]
   
   
7. “Large-Scale Text Categorization by Batch Mode Active Learning,” Steven C. H. Hoi, Rong Jin, Michael R. Lyu, in Proceedings of the 15th International Conference on World Wide Web (WWW2006), pp. 633-642, Edinburgh, The United Kingdom, May 23 - May 26, 2006.
   Paper [DS]
   
   
8. “CUHK at ImageCLEF 2005: Cross-Language and Cross-Media Image Retrieval,” Steven C. H. Hoi, Jianke Zhu, Michael R. Lyu, in Proceedings of the 6th Workshop of the Cross-Language Evalution Forum: Accessing Multilingual Information Repositories (CLEF2005), pp. 602-611, Vienna, Austria, September 21 - September 23, 2005.
   Paper [MM]
   
   
9. “CUHK Experiments with ImageCLEF 2005,” Steven C. H. Hoi, Jianke Zhu, Michael R. Lyu, in Proceedings of the Working Notes for the 6th Workshop of the Cross-Language Evalution Forum Co-Located with the 9th European Conference on Digital Libraries (CLEF:Working Notes2005), pp. 1-9, Wien, Austria, September 21 - September 22, 2005.
   Paper [MM]
   
   
10. “A Semi-Supervised Active Learning Framework for Image Retrieval,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2005), pp. 302-309, San Diego, USA, June 20 - June 26, 2005.
    Paper [MM]
    
    
11. “Integrating User Feedback Log into Relevance Feedback by Coupled SVM for Content-Based Image Retrieval,” Steven C. H. Hoi, Michael R. Lyu, Rong Jin, in Proceedings of the 21st International Conference on Data Engineering Workshops (ICDEW2005), pp. 1-10, Tokyo, Japan, April 5 - April 8, 2005.
    Paper [ML]
    
    
12. “A Novel Log-Based Relevance Feedback Technique in Content-Based Image Retrieval,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 12th ACM International Conference on Multimedia (ACMMM2004), pp. 24-31, New York, USA, October 10 - October 16, 2004.
    Paper [MM]
    
    
13. “Group-Based Relevance Feedback with Support Vector Machine Ensembles,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 17th International Conference on Pattern Recognition (ICPR2004), pp. 874-877, Cambridge, The United Kingdom, August 23 - August 26, 2004.
    Paper [MM]
    
    
14. “Biased Support Vector Machine for Relevance Feedback in Image Retrieval,” Steven C. H. Hoi, Chi-Hang Chan, Kaizhu Huang, Michael R. Lyu, Irwin King, in Proceedings of the 2004 IEEE International Joint Conference on Neural Networks (IJCNN2004), pp. 3189-3194, Budapest, Hungary, July 25 - July 29, 2004.
    Paper [ML]
    
    
15. “Robust Face Recognition Using Minimax Probability Machine,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2004 IEEE International Conference on Multimedia and Expo (ICME2004), pp. 1175-1178, Taipei, Taiwan, June 27 - June 30, 2004.
    Paper [MM]
    
    
16. “Web Image Learning for Searching Semantic Concepts in Image Databases,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 13th international conference on World Wide Web: Alternate Track Papers & Posters (WWW:ATPP2004), pp. 406-407, New York, USA, May 17 - May 20, 2004.
    Paper [DS]
    
    
17. “A Novel Scheme for Video Similarity Detection,” Steven C. H. Hoi, Wei Wang, Michael R. Lyu, in Proceedings of the 2nd International Conference on Image and Video Retrieval (CIVR2003), pp. 373-382, Urbana-Champaign, USA, July 24 - July 25, 2003.
    Paper [MM]
    
    

Graduated in 2006
Residential Real Estate Broker, Royal LePage, Canada
URL: https://dl.acm.org/profile/81100430295
Email: xcai@cse.cuhk.edu.hk

“Coverage-Based Testing Strategies and Reliability Modeling for Fault-Tolerant Software Systems” Thesis Presentation

1. “The Effect of Code Coverage on Fault Detection under Different Testing Profiles,” Xia Cai, Michael R. Lyu, ACM SIGSOFT Software Engineering Notes (SEN), vol. 30, no. 4, pp. 1-7, 2005.
   Paper [SE]
   
   
2. “A Generic Environment for COTS Testing and Quality Prediction,” Xia Cai, Michael R. Lyu, Kam-Fai Wong, in Testing Commercial-off-the-Shelf Components and Systems, pp. 315-347, Published by Springer, 2005.
   Paper [SE]
   
   
3. “Component-Based Embedded Software Engineering: Development Framework, Quality Assurance and a Generic Assessment Environment,” Xia Cai, Michael R. Lyu, Kam-Fai Wong, International Journal of Software Engineering and Knowledge Engineering (IJSEKE), vol. 12, no. 2, pp. 107-133, 2002.
   Paper [SE]
   
   

1. “Software Reliability Modeling with Test Coverage: Experimentation and Measurement with a Fault-Tolerant Software Project,” Xia Cai, Michael R. Lyu, in Proceedings of the 18th IEEE International Symposium on Software Reliability Engineering (ISSRE2007), pp. 17-26, Trollhattan, Sweden, November 5 - November 9, 2007.
   Paper [SE]
   
   
2. “An Experimental Evaluation on Reliability Features of N-Version Programming,” Xia Cai, Michael R. Lyu, Mladen A. Vouk, in Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering (ISSRE2005), pp. 161-170, Chicago, USA, November 8 - November 11, 2005.
   Paper [SE]
   
   
3. “The Effect of Code Coverage on Fault Detection under Different Testing Profiles,” Xia Cai, Michael R. Lyu, in Proceedings of the 27th ACM/IEEE International Conference on Software Engineering: Workshop on Advances in Model-Based Software Testing (ICSE:A-MOST2005), pp. 1-7, St. Louis, USA, May 15 - May 16, 2005.
   Paper [SE]
   
   
4. “An Empirical Study on Reliability Modeling for Diverse Software Systems,” Xia Cai, Michael R. Lyu, in Proceedings of the 15th IEEE International Symposium on Software Reliability Engineering (ISSRE2004), pp. 125-136, Saint-Malo, France, November 2 - November 5, 2004.
   Paper [SE]
   
   
5. “ComPARE: A Generic Quality Assessment Environment for Component-Based Software Systems,” Xia Cai, Michael R. Lyu, Kam-Fai Wong, Mabel Wong, in Proceedings of the 2001 International Symposium on Information Systems and Engineering (ISE2001), pp. 348-354, Las Vegas, USA, June 25 - June 28, 2001.
   Paper [SE]
   
   
6. “Component-Based Software Engineering: Technologies, Development Frameworks, and Quality Assurance Schemes,” Xia Cai, Michael R. Lyu, Kam-Fai Wong, Roy Ko, in Proceedings of the 7th Asia-Pacific Software Engineering Conference (APSEC2000), pp. 372-, Singapore, Singapore, December 5 - December 8, 2000.
   Paper [SE]
   
   

Graduated in 2005
Research, Founder, China
URL: https://dl.acm.org/profile/81100107669
Email: xychen@cse.cuhk.edu.hk

“On Fault Tolerance, Performance, and Reliability for Wireless and Sensor Networks” Thesis Presentation

1. “Reliability Analysis for Various Communication Schemes in Wireless CORBA,” Xinyu Chen, Michael R. Lyu, IEEE Transactions on Reliability (TR), vol. 54, no. 2, pp. 232-242, 2005.
   Paper [SE]
   
   

1. “Voronoi-Based Sleeping Configuration in Wireless Sensor Networks with Location Error,” Xinyu Chen, Michael R. Lyu, Ping Guo, in Proceedings of the IEEE International Conference on Networking, Sensing and Control (ICNSC2008), pp. 1459-1464, Hainan, China, April 6 - April 8, 2008.
   Paper [DS]
   
   
2. “Message Queueing Analysis in Wireless Networks with Mobile Station Failures and Handoffs,” Xinyu Chen, Michael R. Lyu, in Proceedings of the 2004 IEEE Aerospace Conference (Aerospace2004), pp. 1296-1304, Big Sky, Montana, USA, March 6 - March 13, 2004.
   Paper [DS]
   
   
3. “Expected-Reliability Analysis for Wireless CORBA with Imperfect Components,” Xinyu Chen, Michael R. Lyu, in Proceedings of the 10th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC2004), pp. 207-215, Papeete, Tahiti, March 3 - March 5, 2004.
   Paper [SE]
   
   
4. “Performance and Effectiveness Analysis of Checkpointing in Mobile Environments,” Xinyu Chen, Michael R. Lyu, in Proceedings of the 22nd Symposium on Reliable Distributed Systems (SRDS2003), pp. 131-140, Florence, Italy, October 6 - October 8, 2003.
   Paper [DS]
   
   
5. “Message Logging and Recovery in Wireless CORBA Using Access Bridge,” Xinyu Chen, Michael R. Lyu, in Proceedings of the 6th International Symposium on Autonomous Decentralized Systems (ISADS2003), pp. 107-114, Pisa, Italy, April 9 - April 11, 2003.
   Paper [DS]
   
   

Graduated in 2004
Professor, Xi'an Jiaotong Liverpool University, China
URL: https://www.xjtlu.edu.cn/en/departments/academic-departments/electrical-and-electronic-engineering/staff/kaizhu-huang
Email: Kaizhu.Huang@xjtlu.edu.cn

“Learning from Data Locally and Globally” Thesis Presentation

1. “Arbitrary Norm Support Vector Machines,” Kaizhu Huang, Danian Zheng, Irwin King, Michael R. Lyu, Neural Computation (NEURCOM), vol. 21, no. 2, pp. 560-582, 2009.
   Paper [ML]
   
   
2. “Machine Learning: Modeling Data Locally and Globally,” Kaizhu Huang, Haiqin Yang, Michael R. Lyu, in Advanced Topics in Science and Technology in China, pp. 1-169, Published by Springer, 2008.
   Paper [ML]
   
   
3. “Maxi-Min Margin Machine: Learning Large Margin Classifiers Locally and Globally,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, IEEE Transactions on Neural Networks (TNN), vol. 19, no. 2, pp. 260-272, 2008.
   Paper [ML]
   
   
4. “A Novel Discriminative Naive Bayesian Network for Classification,” Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu, Zhangbing Zhou, in Bayesian Network Technologies: Applications and Graphical Models, chap. 1, pp. 1-12, Published by IGI Global, 2007.
   Paper [ML]
   
   
5. “Maximizing Sensitivity in Medical Diagnosis Using Biased Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, IEEE Transactions on Biomedical Engineering (TBME), vol. 53, no. 5, pp. 821-831, 2006.
   Paper [ML]
   
   
6. “Imbalanced Learning with a Biased Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 36, no. 4, pp. 913-923, 2006.
   Paper [ML]
   
   
7. “Local Learning vs. Global Learning: An Introduction to Maxi-Min Margin Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Support Vector Machines: Theory and Applications, pp. 113-131, Published by Springer, 2005.
   Paper [ML]
   
   
8. “The Minimum Error Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan, Journal of Machine Learning Research (JMLR), vol. 5, pp. 1253-1286, 2004.
   Paper [ML]
   
   
9. “Improving Chow-Liu Tree Performance by Mining Association Rules,” Kaizhu Huang, Irwin King, Michael R. Lyu, Haiqin Yang, in Neural Information Processing: Research and Development, pp. 94-112, Published by Springer, 2004.
   Paper [ML]
   
   

1. “Supervised Self-Taught Learning: Actively Transferring Knowledge from Unlabeled Data,” Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu, Colin Campbell, in Proceedings of the 2009 IEEE International Joint Conference on Neural Networks (IJCNN2009), pp. 1272-1277, Atlanta, USA, June 14 - June 19, 2009.
   Paper [ML]
   
   
2. “Semi-Supervised Learning from General Unlabeled Data,” Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Data Mining (ICDM2008), pp. 273-282, Pisa, Italy, December 15 - December 19, 2008.
   Paper [ML]
   
   
3. “Direct Zero-Norm Optimization for Feature Selection,” Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Data Mining (ICDM2008), pp. 845-850, Pisa, Italy, December 15 - December 19, 2008.
   Paper [ML]
   
   
4. “Local Support Vector Regression for Financial Time Series Prediction,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2006 IEEE International Joint Conference on Neural Networks (IJCNN2006), pp. 1622-1627, Vancouver, Canada, July 16 - July 21, 2006.
   Paper [ML]
   
   
5. “Improving Naive Bayesian Classifier by Discriminative Training,” Kaizhu Huang, Zhangbing Zhou, Irwin King, Michael R. Lyu, in Proceedings of the 12th International Conference on Neural Information Processing (ICONIP2005), pp. 49-54, Taipei, Taiwan, October 30 - November 2, 2005.
   Paper [ML]
   
   
6. “Learning Large Margin Classifiers Locally and Globally,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 21st International Conference on Machine Learning (ICML2004), Banff, Canada, July 4 - July 8, 2004.
   Paper [ML]
   
   
7. “Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2004), pp. 558-563, Washington DC, USA, June 27 - July 2, 2004.
   Paper [MM]
   
   
8. “Biased Minimax Probability Machine for Medical Diagnosis,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan, in Proceedings of the 8th International Symposium on Artificial Intelligence and Mathematics (ISAIM2004), Fort Lauderdale, USA, January 4 - January 6, 2004.
   Paper [ML]
   
   
9. “Discriminative Training of Bayesian Chow-Liu Multinet Classifiers,” Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the 2003 IEEE International Joint Conference on Neural Networks (IJCNN2003), pp. 484-488, Portland, USA, July 20 - July 24, 2003.
   Paper [ML]
   
   
10. “Finite Mixture Model of Bounded Semi-Naive Bayesian Networks Classifier,” Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the Joint International Conference on Artificial Neural Networks and Neural Information Processing (ICANN/ICONIP2003), pp. 115-122, Istanbul, Turkey, June 26 - June 29, 2003.
    Paper [ML]
    
    
11. “Constructing a Large Node Chow-Liu Tree Based On Frequent Itemsets,” Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the 9th International Conference on Neural Information Processing (ICONIP2002), pp. 498-502, Singapore, Singapore, November 18 - November 22, 2002.
    Paper [ML]
    
    
12. “Learning Maximum Likelihood Semi-Naive Bayesian Network Classifier,” Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the 2002 IEEE International Conference on Systems, Man and Cybernetics (SMC2002), pp. 1-6, Yasmine Hammamet, Tunisia, October 6 - October 9, 2002.
    Paper [ML]
    
    

Graduated in 2002
Professor, Beijing Normal University, China
URL: http://www.cse.cuhk.edu.hk/~lyu/student/phd/pguo/pguo/Default%20page_files/appsrv.cse.cuhk.edu.hk/~pguo/index.html
Email: pguo@bnu.edu.cn

“Studies of Model Selection and Regularization for Generalization in Neural Networks with Applications” Thesis Presentation

1. “A Study of Regularized Gaussian Classifier in High-Dimension Small Sample Set Case Based on MDL Principle with Application to Spectrum Recognition,” Ping Guo, Yunde Jia, Michael R. Lyu, Pattern Recognition (PR), vol. 41, no. 9, pp. 2842-2854, 2008.
   Paper [MM]
   
   
2. “Blind Image Restoration by Combining Wavelet Transform and RBF Neural Network,” Ping Guo, Hongzhai Li, Michael R. Lyu, International Journal of Wavelets, Multiresolution and Information Processing (IJWMIP), vol. 5, no. 1, pp. 15-26, 2007.
   Paper [ML]
   
   
3. “A Pseudoinverse Learning Algorithm for Feedforward Neural Networks with Stacked Generalization Applications to Software Reliability Growth Data,” Ping Guo, Michael R. Lyu, Neurocomputing (NEUROCOMPUTING), vol. 56, pp. 101-121, 2004.
   Paper [ML]
   
   
4. “Regularization Parameter Estimation for Feedforward Neural Networks,” Ping Guo, Michael R. Lyu, C. L. Philip Chen, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 33, no. 1, pp. 35-44, 2003.
   Paper [ML]
   
   
5. “Cluster Number Selection for a Small Set of Samples Using the Bayesian Ying-Yang model,” Ping Guo, C. L. Philip Chen, Michael R. Lyu, IEEE Transactions on Neural Networks (TNN), vol. 13, no. 3, pp. 757-763, 2002.
   Paper [ML]
   
   
6. “Pseudoinverse Learning Algorithm for Feedfoword Neural Networks,” Ping Guo, Michael R. Lyu, in Advances in Neural Networks and Applications, pp. 321-326, Published by World Scientific and Engineering Academy and Society, 2001.
   Paper [ML]
   
   

1. “A Case Study on Stacked Generalization with Software Reliability Growth Modeling Data,” Ping Guo, Michael R. Lyu, in Proceedings of the 8th International Conference on Neural Information Processing (ICONIP2001), pp. 1321-1326, Shanghai, China, November 14 - November 18, 2001.
   Paper [ML]
   
   
2. “Software Quality Prediction Using Mixture Models with EM Algorithm,” Ping Guo, Michael R. Lyu, in Proceedings of the 1st Asia-Pacific Conference on Quality Software (APAQS2000), pp. 69-80, Hong Kong, China, October 30 - October 31, 2000.
   Paper [SE]
   
   
3. “A Study on Color Space Selection for Determining Image Segmentation Region Number,” Ping Guo, Michael R. Lyu, in Proceedings of the 2000 International Conference on Internet Computing (IC2000), pp. 1127-1132, Las Vegas, USA, June 26 - June 29, 2000.
   Paper [DS]
   
   
4. “Classification for High-Dimension Small-Sample Data Sets Based on Kullback-Leibler Information Measure,” Ping Guo, Michael R. Lyu, in Proceedings of the 2000 International Conference on Artificial Intelligence (ICAI2000), pp. 1187-1193, Las Vegas, USA, June 26 - June 29, 2000.
   Paper [ML]