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 at Carnegie Mellon University; Chief Scientific Officer at AbridgeVerified email at cmu.edu
Asli CelikyilmazResearcher @ FAIR at Meta AIVerified email at ieee.org
Dale SchuurmansResearch Scientist, Google Brain / Professor, University of AlbertaVerified email at cs.ualberta.ca
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, PhDMicrosoftVerified email at microsoft.com
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
Xiaodong He (何晓冬)AI Lab, JD.COM (京东AI研究院); IEEE/CAAI FellowVerified email at ieee.org

Lihong Li (李力鸿)

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Reinforcement Learning Machine Learning Artificial Intelligence


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	2753	2010
Parallelized stochastic gradient descent M Zinkevich, M Weimer, L Li, A Smola Advances in neural information processing systems 23, 2010	1516	2010
An empirical evaluation of thompson sampling O Chapelle, L Li Advances in neural information processing systems 24, 2011	1508	2011
Contextual bandits with linear payoff functions W Chu, L Li, L Reyzin, R Schapire Proceedings of the Fourteenth International Conference on Artificial …, 2011	938	2011
Neural approaches to conversational AI J Gao, M Galley, L Li The 41st International ACM SIGIR Conference on Research & Development in …, 2018	698	2018
Doubly robust policy evaluation and learning M Dudík, J Langford, L Li arXiv preprint arXiv:1103.4601, 2011	622	2011
Doubly Robust Policy Evaluation and Learning M Dudık, J Langford, L Li	622*
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	603	2011
Sparse Online Learning via Truncated Gradient. J Langford, L Li, T Zhang Journal of Machine Learning Research 10 (3), 2009	565	2009
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	555	2006
Doubly robust off-policy value evaluation for reinforcement learning N Jiang, L Li International Conference on Machine Learning, 652-661, 2016	530	2016
Towards a unified theory of state abstraction for MDPs. L Li, TJ Walsh, ML Littman AI&M, 2006	480	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	463	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	420*	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	378	2017
Neuro-symbolic program synthesis E Parisotto, A Mohamed, R Singh, L Li, D Zhou, P Kohli arXiv preprint arXiv:1611.01855, 2016	341	2016
Reinforcement Learning in Finite MDPs: PAC Analysis. AL Strehl, L Li, ML Littman Journal of Machine Learning Research 10 (11), 2009	335	2009
Contextual bandit algorithms with supervised learning guarantees A Beygelzimer, J Langford, L Li, L Reyzin, RE Schapire Arxiv preprint arXiv:1002.4058, 2010	292	2010
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	291	2008
Breaking the curse of horizon: Infinite-horizon off-policy estimation Q Liu, L Li, Z Tang, D Zhou Advances in Neural Information Processing Systems 31, 2018	268	2018

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