Explainable Machine Learning with Interactive Visualization
|Title:||Explainable Machine Learning with Interactive Visualization|
|Date:||September 11, 2018 (Tuesday)|
|Time:||2:00 pm - 3:00 pm|
|Venue:||Room 121, 1/F, Ho Sin-hang Engineering Building, The Chinese University of Hong Kong, Shatin, N.T.|
|Speaker:|| Prof. Shixia LIU
Machine learning has demonstrated to be highly successful at solving many real-world applications ranging from information retrieval, data mining, and speech recognition, to computer graphics, visualization, and human-computer interaction. However, most users often treat the machine learning model as a “black box” because of its incomprehensible functions and unclear working mechanism. Without a clear understanding of how and why the model works, the development of high-performance models typically relies on a time-consuming trial-and-error procedure. This talk presents the major challenges of explainable machine learning and exemplifies the solutions with several visual analytics techniques and examples, including model understanding and diagnosis.
Shixia Liu is a tenured associate professor at Tsinghua University. Her research interests include explainable machine learning, visual text analytics, visual social analytics, and text mining. Before joining Tsinghua University, she worked as a lead researcher at Microsoft Research Asia and a research staff member at IBM China Research Lab. Shixia is one of the Papers Co-Chairs of IEEE VAST 2016 and 2017. She is an associate of IEEE Transactions on Visualization and Computer Graphics and IEEE Transactions on Big data. She is on the editorial board of Information Visualization and Journal of visualization. She was the guest editor of ACM Transactions on Intelligent Systems and Technology and Tsinghua Science and Technology. She was the program co-chair of PacifcVis 2014 and VINCI 2012. Shixia was in the Steering Committee of VINCI 2013. She is on the organizing committee of IEEE VIS 2015 and 2014. She is/was in the Program Committee for CHI 2019, 2018, InfoVis 2015, 2014, VAST 2018, 2015, 2014, KDD 2015, 2014, 2013, ACM Multimedia 2009, SDM 2008, ACM IUI 2011, 2009, PacificVis 2008, 2009, 2010, 2011, PAKDD 2013, VISAPP 2012, 2011, VINCI 2011.
Enquiries: Ms. Crystal Tam at tel. 3943 8439
For more information, please refer to http://www.cse.cuhk.edu.hk/en/events
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