- 7Efficient Reinforcement Learning Through Uncertainties10:00 am - 11:00 am
Mr. ZHOU Dongruo
Reinforcement learning (RL) has achieved great empirical success in many real-world problems in the last few years. However, many RL algorithms are inefficient due to their data-hungry nature. Whether there exists a universal way to improve the efficiency of existing RL algorithms re, ...
- 13Designing and Analyzing Machine Learning Algorithms in the Presence of Strategic Behavior10:00 am - 11:00 am
Mr. ZHANG Hanrui
Machine learning algorithms now play a major part in all kinds of decision-making scenarios. When the stakes are high, self-interested agents — about whom decisions are being made — are increasingly tempted to manipulate the machine learning algorithm, in order to better, ...
- 14Clustering Health Care Data11:00 am - 12:00 pm
Prof. Pasi Fränti
School of Computing
University of Eastern Finland
Clustering can be a powerful tool in analyzing healthcare data. We show how clustering algorithms can be used to extract new insight from various health data with the aim to better optimize the future health care system. We first sh, ...
- 15Execution-Guided Learning for Software Development, Testing, and Maintenance10:00 am - 11:00 am
Mr. NIE Pengyu
Machine Learning (ML) techniques have been increasing adopted for Software Engineering (SE) tasks, such as code completion and code summarization. However, existing ML models provide limited value for SE tasks, because these models do not take into account the key characteristics of so, ...Adaptive and Automated Deep Recommender Systems2:00 pm - 3:00 pm
Prof. ZHAO Xiangyu
Assistant Professor, School of Data Science
City University of Hong Kong (CityU)
Deep recommender systems have become increasingly popular in recent years, and have been utilized in a variety of domains, including movies, music, books, search queries, and social networks. They assi, ...
- 17Resilience through Adaptation — the Challenge of Change2:30 pm - 3:30 pm
Professor Jeff Kramer
Emeritus Professor, Department of Computing,
Imperial College London
Change in complex systems is inevitable. Providing rigorous techniques and tools to support dynamic system adaptation so that it can be performed online, at runtime, is certainly challenging. However the potent, ...
- 21Data-Efficient Graph Learning10:00 am - 11:00 am
Mr. DING Kaize
The world around us — and our understanding of it — is rich in relational structure: from atoms and their interactions to objects and entities in our environments. Graphs, with nodes representing entities and edges representing relationships between entities, serve as a com, ...
- 24Deep Learning for Physical Design Automation of VLSI Circuits: Modeling, Optimization, and Datasets3:00 pm - 4:00 pm
Professor Yibo Lin
School of Integrated Circuits
Physical design is a critical step in the design flow of modern VLSI circuits. With continuous increase of design complexity, physical design becomes extremely challenging and time-consuming due to the repeated des, ...
- 30Huawei Seminar (in Mandarin)10:00 am - 11:00 am
6 lab managers from Huawei Cloud will hold a presentation and communication session in the Room 121, HSH Engineering Building at the Chinese University of Hong Kong on March 30th, from 10 – 11 am. They will introduce the following six innovative Labs from Huawei Cloud:
- Algorithm Innovation Lab: Application of ma
- 31Demystifying Fuzzing Strategies8:00 am - 6:00 pm
Professor Yuqun Zhang
Department of Computer Science and Engineering
Southern University of Science and Technology
Fuzzing (or fuzz testing) refers to inputting invalid, unexpected, or random data to programs for exposing unexpected program behaviors (such as crashes, failing asse, ...