Search Machine Learning Repository:
All publications by Lihong Li
authors venues years



PAC-inspired Option Discovery in Lifelong Reinforcement Learning
Emma Brunskill and Lihong Li
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hsu, Satyen Kale, John Langford, Lihong Li and Robert Schapire
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


An Empirical Evaluation of Thompson Sampling
Olivier Chapelle and Lihong Li
Advances in Neural Information Processing Systems 24, 2011


Doubly Robust Policy Evaluation and Learning
John Langford, Lihong Li and Miroslav Dudík
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Contextual Bandits with Linear Payoff Functions
Wei Chu, Lihong Li, Lev Reyzin and Robert E. Schapire
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Contextual Bandit Algorithms with Supervised Learning Guarantees
Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin and Robert E. Schapire
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Linear-Time Estimators for Propensity Scores
Deepak Agarwal, Lihong Li and Alex J. Smola
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Parallelized Stochastic Gradient Descent
Martin Zinkevich, Markus Weimer, Lihong Li and Alex J. Smola
Advances in Neural Information Processing Systems 23, 2010


Learning from Logged Implicit Exploration Data
Alex Strehl, John Langford, Lihong Li and Sham M. Kakade
Advances in Neural Information Processing Systems 23, 2010


Sparse Online Learning via Truncated Gradient
John Langford, Lihong Li and Tong Zhang
Journal of Machine Learning Research, 2009


Provably Efficient Learning with Typed Parametric Models
Emma Brunskill, Bethany R. Leffler, Lihong Li, Michael L. Littman and Nicholas Roy
Journal of Machine Learning Research, 2009


Reinforcement Learning in Finite MDPs: PAC Analysis
Alexander L. Strehl, Lihong Li and Michael L. Littman
Journal of Machine Learning Research, 2009


Workshop summary: Results of the 2009 reinforcement learning competition
David Wingate, Carlos Diuk, Lihong Li, Matthew Taylor and Jordan Frank
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


The adaptive {\it k}-meteorologists problem and its application to structure learning and feature selection in reinforcement learning
Carlos Diuk, Lihong Li and Bethany R. Leffler
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning
Ronald Parr, Lihong Li, Gavin Taylor, Christopher Painter-wakefield and Michael L. Littman
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Knows what it knows: a framework for self-aware learning
Lihong Li, Michael L. Littman and Thomas J. Walsh
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


A worst-case comparison between temporal difference and residual gradient with linear function approximation
Lihong Li
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Sparse Online Learning via Truncated Gradient
John Langford, Lihong Li and Tong Zhang
Advances in Neural Information Processing Systems 21, 2008


Analyzing feature generation for value-function approximation
Ronald Parr, Christopher Painter-wakefield, Lihong Li and Michael L. Littman
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


PAC model-free reinforcement learning
Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford and Michael L. Littman
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006