| 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 | 1775 | 2010 |
| Parallelized stochastic gradient descent M Zinkevich, M Weimer, L Li, AJ Smola Advances in neural information processing systems, 2595-2603, 2010 | 1102 | 2010 |
| An empirical evaluation of thompson sampling O Chapelle, L Li Advances in neural information processing systems, 2249-2257, 2011 | 1001 | 2011 |
| Contextual bandits with linear payoff functions W Chu, L Li, L Reyzin, R Schapire Proceedings of the Fourteenth International Conference on Artificial …, 2011 | 568 | 2011 |
| Sparse Online Learning via Truncated Gradient. J Langford, L Li, T Zhang Journal of Machine Learning Research 10 (3), 2009 | 502 | 2009 |
| 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 | 440 | 2011 |
| 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 | 422 | 2006 |
| Doubly robust policy evaluation and learning M Dudík, J Langford, L Li arXiv preprint arXiv:1103.4601, 2011 | 370 | 2011 |
| Doubly Robust Policy Evaluation and Learning M Dudık, J Langford, L Li | 370* | |
| Towards a Unified Theory of State Abstraction for MDPs. L Li, TJ Walsh, ML Littman ISAIM, 2006 | 318 | 2006 |
| Neural approaches to conversational AI J Gao, M Galley, L Li The 41st International ACM SIGIR Conference on Research & Development in …, 2018 | 309 | 2018 |
| 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 | 296 | 2014 |
| Reinforcement Learning in Finite MDPs: PAC Analysis. AL Strehl, L Li, ML Littman Journal of Machine Learning Research 10 (11), 2009 | 271 | 2009 |
| 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 | 263 | 2008 |
| Doubly robust off-policy value evaluation for reinforcement learning N Jiang, L Li International Conference on Machine Learning, 652-661, 2016 | 252 | 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 | 244 | 2017 |
| 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 | 235 | 2016 |
| Neuro-symbolic program synthesis E Parisotto, A Mohamed, R Singh, L Li, D Zhou, P Kohli arXiv preprint arXiv:1611.01855, 2016 | 207 | 2016 |
| Contextual bandit algorithms with supervised learning guarantees A Beygelzimer, J Langford, L Li, L Reyzin, RE Schapire Arxiv preprint arXiv:1002.4058, 2010 | 195 | 2010 |
| 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 | 194 | 2008 |
John LangfordMicrosoft Research New YorkVerified email at hunch.net
