Lihong Li (李力鸿)

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John LangfordMicrosoft Research New YorkVerified email at hunch.net
Michael LittmanBrown UniversityVerified email at brown.edu
Jianfeng GaoMicrosoft Research, RedmondVerified email at microsoft.com
Wei Chu（褚崴）AlibabaVerified email at gatsby.ucl.ac.uk
Li DengChief AI Officer, Citadel (former)Verified email at ieee.org
Robert SchapireMicrosoft ResearchVerified email at microsoft.com
Bo DaiResearch Scientist, Google BrainVerified email at google.com
Jianshu ChenTencent AI LabVerified email at ucla.edu
Denny ZhouResearch Scientist, Google BrainVerified email at google.com
Zachary C. LiptonAssistant Professor of Machine Learning at CMUVerified email at cmu.edu
Dale SchuurmansResearch Scientist, Google Brain / Professor, University of AlbertaVerified email at cs.ualberta.ca
Asli CelikyilmazResearcher @ FAIR at Meta AIVerified email at ieee.org
Yun-Nung (Vivian) ChenNational Taiwan UniversityVerified email at ieee.org
Thomas J. WalshSony AIVerified email at sony.com
Emma BrunskillAssociate Professor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Faisal Ahmed, PhDSUNY Stony BrookVerified email at cs.stonybrook.edu
Csaba SzepesvariDeepMind & University of AlbertaVerified email at cs.ualberta.ca
Xiujun LiComputer Science & Engineering, University of WashingtonVerified email at cs.washington.edu
Ronald ParrProfessor of Computer Science, Duke UniversityVerified email at cs.duke.edu
Lev ReyzinProfessor of Mathematics, Statistics, and Computer Science; University of Illinois at ChicagoVerified email at uic.edu

Lihong Li (李力鸿)

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Reinforcement Learning Machine Learning Artificial Intelligence


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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	2516	2010
Parallelized stochastic gradient descent M Zinkevich, M Weimer, L Li, A Smola Advances in neural information processing systems 23, 2010	1416	2010
An empirical evaluation of thompson sampling O Chapelle, L Li Advances in neural information processing systems 24, 2011	1381	2011
Contextual bandits with linear payoff functions W Chu, L Li, L Reyzin, R Schapire Proceedings of the Fourteenth International Conference on Artificial …, 2011	836	2011
Neural approaches to conversational ai J Gao, M Galley, L Li Foundations and trends® in information retrieval 13 (2-3), 127-298, 2019	589	2019
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	566	2011
Sparse Online Learning via Truncated Gradient. J Langford, L Li, T Zhang Journal of Machine Learning Research 10 (3), 2009	539	2009
Doubly robust policy evaluation and learning M Dudík, J Langford, L Li arXiv preprint arXiv:1103.4601, 2011	522	2011
Doubly Robust Policy Evaluation and Learning M Dudık, J Langford, L Li	522*
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	515	2006
Doubly robust off-policy value evaluation for reinforcement learning N Jiang, L Li International Conference on Machine Learning, 652-661, 2016	433	2016
Towards a Unified Theory of State Abstraction for MDPs. L Li, TJ Walsh, ML Littman AI&M, 2006	426	2006
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	398	2014
Towards end-to-end reinforcement learning of dialogue agents for information access B Dhingra, L Li, X Li, J Gao, YN Chen, F Ahmed, L Deng arXiv preprint arXiv:1609.00777, 2016	382*	2016
End-to-end task-completion neural dialogue systems X Li, YN Chen, L Li, J Gao, A Celikyilmaz arXiv preprint arXiv:1703.01008, 2017	340	2017
Reinforcement Learning in Finite MDPs: PAC Analysis. AL Strehl, L Li, ML Littman Journal of Machine Learning Research 10 (11), 2009	318	2009
Neuro-symbolic program synthesis E Parisotto, A Mohamed, R Singh, L Li, D Zhou, P Kohli arXiv preprint arXiv:1611.01855, 2016	299	2016
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	278	2008
Contextual bandit algorithms with supervised learning guarantees A Beygelzimer, J Langford, L Li, L Reyzin, RE Schapire Arxiv preprint arXiv:1002.4058, 2010	258	2010
Deep reinforcement learning with a natural language action space J He, J Chen, X He, J Gao, L Li, L Deng, M Ostendorf arXiv preprint arXiv:1511.04636, 2015	232*	2015

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