Lihong Li (李力鸿)
Lihong Li (李力鸿)
Research Scientist, Google
Verified email at google.com - Homepage
TitleCited byYear
A contextual-bandit approach to personalized news article recommendation
L Li, W Chu, J Langford, RE Schapire
Proceedings of the 19th international conference on World wide web, 661-670, 2010
12042010
Parallelized stochastic gradient descent
M Zinkevich, M Weimer, L Li, AJ Smola
Advances in neural information processing systems, 2595-2603, 2010
8102010
An empirical evaluation of thompson sampling
O Chapelle, L Li
Advances in neural information processing systems, 2249-2257, 2011
6922011
Sparse online learning via truncated gradient
J Langford, L Li, T Zhang
Journal of Machine Learning Research 10 (Mar), 777-801, 2009
4252009
Contextual bandits with linear payoff functions
W Chu, L Li, L Reyzin, R Schapire
Proceedings of the Fourteenth International Conference on Artificial …, 2011
3542011
Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms
L Li, W Chu, J Langford, X Wang
Proceedings of the fourth ACM international conference on Web search and …, 2011
3212011
PAC model-free reinforcement learning
AL Strehl, L Li, E Wiewiora, J Langford, ML Littman
Proceedings of the 23rd international conference on Machine learning, 881-888, 2006
3112006
Towards a Unified Theory of State Abstraction for MDPs.
L Li, TJ Walsh, ML Littman
ISAIM, 2006
2412006
Doubly robust policy evaluation and learning
M Dudík, J Langford, L Li
arXiv preprint arXiv:1103.4601, 2011
2172011
Doubly Robust Policy Evaluation and Learning
M Dudık, J Langford, L Li
217*
Taming the monster: A fast and simple algorithm for contextual bandits
A Agarwal, D Hsu, S Kale, J Langford, L Li, R Schapire
International Conference on Machine Learning, 1638-1646, 2014
2092014
Knows what it knows: a framework for self-aware learning
L Li, ML Littman, TJ Walsh
Proceedings of the 25th international conference on Machine learning, 568-575, 2008
2012008
Reinforcement learning in finite MDPs: PAC analysis
AL Strehl, L Li, ML Littman
Journal of Machine Learning Research 10 (Nov), 2413-2444, 2009
1972009
A Bayesian sampling approach to exploration in reinforcement learning
J Asmuth, L Li, ML Littman, A Nouri, D Wingate
Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial …, 2009
1522009
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning
R Parr, L Li, G Taylor, C Painter-Wakefield, ML Littman
Proceedings of the 25th international conference on Machine learning, 752-759, 2008
1522008
Analyzing feature generation for value-function approximation
R Parr, C Painter-Wakefield, L Li, M Littman
Proceedings of the 24th international conference on Machine learning, 737-744, 2007
1472007
Contextual bandit algorithms with supervised learning guarantees
A Beygelzimer, J Langford, L Li, L Reyzin, RE Schapire
Arxiv preprint arXiv:1002.4058, 2010
1392010
Doubly robust off-policy value evaluation for reinforcement learning
N Jiang, L Li
arXiv preprint arXiv:1511.03722, 2015
1212015
Learning from logged implicit exploration data
A Strehl, J Langford, L Li, SM Kakade
Advances in Neural Information Processing Systems, 2217-2225, 2010
1192010
End-to-end task-completion neural dialogue systems
X Li, YN Chen, L Li, J Gao, A Celikyilmaz
arXiv preprint arXiv:1703.01008, 2017
1172017
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