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Author Information
Xinhua Zhang (University of Illinois at Chicago (UIC))
Wee Sun Lee (National University of Singapore)
Wee Sun Lee is a professor in the Department of Computer Science, National University of Singapore. He obtained his B.Eng from the University of Queensland in 1992 and his Ph.D. from the Australian National University in 1996. He has been a research fellow at the Australian Defence Force Academy, a fellow of the Singapore-MIT Alliance, and a visiting scientist at MIT. His research interests include machine learning, planning under uncertainty, and approximate inference. His works have won the Test of Time Award at Robotics: Science and Systems (RSS) 2021, the RoboCup Best Paper Award at International Conference on Intelligent Robots and Systems (IROS) 2015, the Google Best Student Paper Award, Uncertainty in AI (UAI) 2014 (as faculty co-author), as well as several competitions and challenges. He has been an area chair for machine learning and AI conferences such as the Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), the AAAI Conference on Artificial Intelligence (AAAI), and the International Joint Conference on Artificial Intelligence (IJCAI). He was a program, conference and journal track co-chair for the Asian Conference on Machine Learning (ACML), and he is currently the co-chair of the steering committee of ACML.
More from the Same Authors
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2022 : Poisoning Generative Models to Promote Catastrophic Forgetting »
Siteng Kang · Xinhua Zhang -
2022 : Efficient Offline Policy Optimization with a Learned Model »
Zichen Liu · Siyi Li · Wee Sun Lee · Shuicheng Yan · Zhongwen Xu -
2022 : Continual Poisoning of Generative Models to Promote Catastrophic Forgetting »
Siteng Kang · Xinhua Zhang -
2022 Poster: Moment Distributionally Robust Tree Structured Prediction »
Yeshu Li · Danyal Saeed · Xinhua Zhang · Brian Ziebart · Kevin Gimpel -
2022 Poster: Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats »
Hongwei Jin · Zishun Yu · Xinhua Zhang -
2021 Poster: Distributionally Robust Imitation Learning »
Mohammad Ali Bashiri · Brian Ziebart · Xinhua Zhang -
2021 Poster: Implicit Task-Driven Probability Discrepancy Measure for Unsupervised Domain Adaptation »
Mao Li · Kaiqi Jiang · Xinhua Zhang -
2021 : Part 4: Appendix: Proofs and Derivations »
Wee Sun Lee -
2021 : Part 3: Graph Neural Networks and Attention Networks »
Wee Sun Lee -
2021 : Part 2: Markov Decision Process »
Wee Sun Lee -
2021 Tutorial: Message Passing In Machine Learning »
Wee Sun Lee -
2021 : Part 1: Message Passing Overview and Probabilistic Graphical Models »
Wee Sun Lee -
2020 Poster: Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks »
Hongwei Jin · Zhan Shi · Venkata Jaya Shankar Ashish Peruri · Xinhua Zhang -
2020 Poster: Factor Graph Neural Networks »
Zhen Zhang · Fan Wu · Wee Sun Lee -
2020 Spotlight: Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks »
Hongwei Jin · Zhan Shi · Venkata Jaya Shankar Ashish Peruri · Xinhua Zhang -
2020 Poster: Proximal Mapping for Deep Regularization »
Mao Li · Yingyi Ma · Xinhua Zhang -
2020 Spotlight: Proximal Mapping for Deep Regularization »
Mao Li · Yingyi Ma · Xinhua Zhang -
2018 Poster: Distributionally Robust Graphical Models »
Rizal Fathony · Ashkan Rezaei · Mohammad Ali Bashiri · Xinhua Zhang · Brian Ziebart -
2017 Poster: Decomposition-Invariant Conditional Gradient for General Polytopes with Line Search »
Mohammad Ali Bashiri · Xinhua Zhang -
2017 Poster: QMDP-Net: Deep Learning for Planning under Partial Observability »
Peter Karkus · David Hsu · Wee Sun Lee -
2017 Poster: Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction »
Zhan Shi · Xinhua Zhang · Yaoliang Yu -
2017 Spotlight: Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction »
Zhan Shi · Xinhua Zhang · Yaoliang Yu -
2016 Poster: Convex Two-Layer Modeling with Latent Structure »
Vignesh Ganapathiraman · Xinhua Zhang · Yaoliang Yu · Junfeng Wen -
2015 Poster: Adaptive Stochastic Optimization: From Sets to Paths »
Zhan Wei Lim · David Hsu · Wee Sun Lee -
2014 Poster: Convex Deep Learning via Normalized Kernels »
Özlem Aslan · Xinhua Zhang · Dale Schuurmans -
2014 Poster: Robust Bayesian Max-Margin Clustering »
Changyou Chen · Jun Zhu · Xinhua Zhang -
2013 Poster: DESPOT: Online POMDP Planning with Regularization »
Adhiraj Somani · Nan Ye · David Hsu · Wee Sun Lee -
2013 Poster: Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space »
Xinhua Zhang · Wee Sun Lee · Yee Whye Teh -
2013 Spotlight: Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space »
Xinhua Zhang · Wee Sun Lee · Yee Whye Teh -
2013 Poster: Convex Two-Layer Modeling »
Özlem Aslan · Hao Cheng · Xinhua Zhang · Dale Schuurmans -
2013 Spotlight: Convex Two-Layer Modeling »
Özlem Aslan · Hao Cheng · Xinhua Zhang · Dale Schuurmans -
2013 Poster: Polar Operators for Structured Sparse Estimation »
Xinhua Zhang · Yao-Liang Yu · Dale Schuurmans -
2013 Poster: Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion »
Nguyen Viet Cuong · Wee Sun Lee · Nan Ye · Kian Ming Adam Chai · Hai Leong Chieu -
2012 Poster: Convex Multi-view Subspace Learning »
Martha White · Yao-Liang Yu · Xinhua Zhang · Dale Schuurmans -
2012 Poster: Accelerated Training for Matrix-norm Regularization: A Boosting Approach »
Xinhua Zhang · Yao-Liang Yu · Dale Schuurmans -
2011 Poster: Monte Carlo Value Iteration with Macro-Actions »
Zhan Wei Lim · David Hsu · Wee Sun Lee -
2010 Poster: Lower Bounds on Rate of Convergence of Cutting Plane Methods »
Xinhua Zhang · Ankan Saha · S.V.N. Vishwanathan -
2010 Session: Oral Session 2 »
Wee Sun Lee -
2009 Poster: Conditional Random Fields with High-Order Features for Sequence Labeling »
Nan Ye · Wee Sun Lee · Hai Leong Chieu · Dan Wu -
2008 Poster: Kernel Measures of Independence for non-iid Data »
Xinhua Zhang · Le Song · Arthur Gretton · Alexander Smola -
2008 Spotlight: Kernel Measures of Independence for non-iid Data »
Xinhua Zhang · Le Song · Arthur Gretton · Alexander Smola -
2007 Poster: Cooled and Relaxed Survey Propagation for MRFs »
Hai Leong Chieu · Wee Sun Lee · Yee Whye Teh -
2007 Spotlight: Cooled and Relaxed Survey Propagation for MRFs »
Hai Leong Chieu · Wee Sun Lee · Yee Whye Teh -
2007 Spotlight: What makes some POMDP problems easy to approximate? »
David Hsu · Wee Sun Lee · Nan Rong -
2007 Poster: What makes some POMDP problems easy to approximate? »
David Hsu · Wee Sun Lee · Nan Rong