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All publications by Wee S. Lee
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Adaptive Stochastic Optimization: From Sets to Paths
Zhan W. Lim, David Hsu and Wee S. Lee
Advances in Neural Information Processing Systems 28, 2015


Covering Number for Efficient Heuristic-based POMDP Planning
Zongzhang Zhang, David Hsu and Wee S. Lee
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


DESPOT: Online POMDP Planning with Regularization
Adhiraj Somani, Nan Ye, David Hsu and Wee S. Lee
Advances in Neural Information Processing Systems 26, 2013


Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion
Nguyen V. Cuong, Wee S. Lee, Nan Ye, Kian Chai and Hai L. Chieu
Advances in Neural Information Processing Systems 26, 2013


Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space
Xinhua Zhang, Wee S. Lee and Yee W. Teh
Advances in Neural Information Processing Systems 26, 2013


Monte Carlo Bayesian Reinforcement Learning
Yi Wang, Kok S. Won, Wee S. Lee and Daniel J. Hsu
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Optimizing F-measure: A Tale of Two Approaches
Ye Nan, Kian M. Chai, Wee S. Lee and Hai L. Chieu
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Conditional Random Fields with High-Order Features for Sequence Labeling
Nan Ye, Wee S. Lee, Hai L. Chieu and Dan Wu
Advances in Neural Information Processing Systems 22, 2009


Cooled and Relaxed Survey Propagation for MRFs
Hai L. Chieu, Wee S. Lee and Yee W. Teh
Advances in Neural Information Processing Systems 20, 2007


What makes some POMDP problems easy to approximate?
Wee S. Lee, Nan Rong and Daniel J. Hsu
Advances in Neural Information Processing Systems 20, 2007


Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms
Xinhua Zhang and Wee S. Lee
Advances in Neural Information Processing Systems 19, 2006


Learning with Positive and Unlabeled Examples Using Weighted Logistic Regression
Wee S. Lee and Bing Liu
Proceedings of the 20th International Conference on Machine Learning (ICML-03), 2003