Seuraa
Lihong Li (李力鸿)
Lihong Li (李力鸿)
Amazon
Vahvistettu sähköpostiosoite verkkotunnuksessa amazon.com - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
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
25212010
Parallelized stochastic gradient descent
M Zinkevich, M Weimer, L Li, A Smola
Advances in neural information processing systems 23, 2010
14162010
An empirical evaluation of thompson sampling
O Chapelle, L Li
Advances in neural information processing systems 24, 2011
13832011
Contextual bandits with linear payoff functions
W Chu, L Li, L Reyzin, R Schapire
Proceedings of the Fourteenth International Conference on Artificial …, 2011
8392011
Neural approaches to conversational ai
J Gao, M Galley, L Li
Foundations and trends® in information retrieval 13 (2-3), 127-298, 2019
5892019
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
5682011
Sparse Online Learning via Truncated Gradient.
J Langford, L Li, T Zhang
Journal of Machine Learning Research 10 (3), 2009
5422009
Doubly robust policy evaluation and learning
M Dudík, J Langford, L Li
arXiv preprint arXiv:1103.4601, 2011
5252011
Doubly Robust Policy Evaluation and Learning
M Dudık, J Langford, L Li
525*
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
5162006
Doubly robust off-policy value evaluation for reinforcement learning
N Jiang, L Li
International Conference on Machine Learning, 652-661, 2016
4342016
Towards a Unified Theory of State Abstraction for MDPs.
L Li, TJ Walsh, ML Littman
AI&M, 2006
4272006
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
3982014
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
3402017
Reinforcement Learning in Finite MDPs: PAC Analysis.
AL Strehl, L Li, ML Littman
Journal of Machine Learning Research 10 (11), 2009
3182009
Neuro-symbolic program synthesis
E Parisotto, A Mohamed, R Singh, L Li, D Zhou, P Kohli
arXiv preprint arXiv:1611.01855, 2016
3002016
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
2792008
Contextual bandit algorithms with supervised learning guarantees
A Beygelzimer, J Langford, L Li, L Reyzin, RE Schapire
Arxiv preprint arXiv:1002.4058, 2010
2602010
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
233*2015
Järjestelmä ei voi suorittaa toimenpidettä nyt. Yritä myöhemmin uudelleen.
Artikkelit 1–20