Friday, November 6 2020, 11am VIrtual Event Colloquia Arthur Choi is a research scientist in the Computer Science Department at the University of California at Los Angeles (UCLA). He obtained his Ph.D. from UCLA in 2010. His research interests are in logical and probabilistic approaches to reasoning, machine learning, tractable knowledge representations, and most recently in explainable artificial intelligence (XAI). He has led medal-winning teams in international probabilistic inference competitions. He has served as an SPC/PC member at conferences such as IJCAI, AAAI, UAI, NeurIPS, and ICML. In this talk, Dr. Choi will propose a symbolic approach to explaining the behavior and verifying the properties of machine learning models, which are based on sustained advances in logical and probabilistic reasoning. He will show how his approach facilitates the analysis of a neural network, helping us to understand its behavior, and in turn, providing directions towards learning better and more robust models. Please use the following link to join the lecture: https://zoom.us/j/7065830827?from=addon. Choi, A._Colloquium Announcement.pdf (362.94 KB) Arthur Choi Department of Computer Science University of California at Los Angeles
