Lihong Li

other persons with the same name:

• Lihong Li 0002

	2012
j16		John Langford, Lihong Li, R. Preston McAfee, Kishore Papineni: Cloud control: voluntary admission control for intranet traffic management. Inf. Syst. E-Business Management 10(3): 295-308 (2012)
j15		Lihong Li, Olivier Chapelle: Open Problem: Regret Bounds for Thompson Sampling. Journal of Machine Learning Research - Proceedings Track 23: 43.1-43.3 (2012)
j14		Lihong Li, Wei Chu, John Langford, Taesup Moon, Xuanhui Wang: Bandits with Generalized Linear Models. Journal of Machine Learning Research - Proceedings Track 26: 19-36 (2012)
j13		Taesup Moon, Wei Chu, Lihong Li, Zhaohui Zheng, Yi Chang: An Online Learning Framework for Refining Recency Search Results with User Click Feedback. ACM Trans. Inf. Syst. 30(4): 20 (2012)
c42		Lihong Li, Yan Gao, Yan Wang: Fuzzy Time Series Forecasting Based on Weber-Fischna Law. ICICA (1) 2012: 329-335
c41		Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li: Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits. UAI 2012: 247-254
c40		Vidhya Navalpakkam, Ravi Kumar, Lihong Li, D. Sivakumar: Attention and Selection in Online Choice Tasks. UMAP 2012: 200-211
c39		Hongning Wang, Anlei Dong, Lihong Li, Yi Chang, Evgeniy Gabrilovich: Joint relevance and freshness learning from clickthroughs for news search. WWW 2012: 579-588
i9		John Asmuth, Lihong Li, Michael L. Littman, Ali Nouri, David Wingate: A Bayesian Sampling Approach to Exploration in Reinforcement Learning. CoRR abs/1205.2664 (2012)
i8		Emma Brunskill, Bethany R. Leffler, Lihong Li, Michael L. Littman, Nicholas Roy: CORL: A Continuous-state Offset-dynamics Reinforcement Learner. CoRR abs/1206.3231 (2012)
i7		Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li: Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits. CoRR abs/1210.4862 (2012)
	2011
j12		Lihong Li, Lihui Zhou, Hongjun Lian: Sea-level Rise Forecast Model. JCP 6(10): 2120-2126 (2011)
j11		Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, Robert E. Schapire: Contextual Bandit Algorithms with Supervised Learning Guarantees. Journal of Machine Learning Research - Proceedings Track 15: 19-26 (2011)
j10		Deepak Agarwal, Lihong Li, Alexander J. Smola: Linear-Time Estimators for Propensity Scores. Journal of Machine Learning Research - Proceedings Track 15: 93-100 (2011)
j9		Wei Chu, Lihong Li, Lev Reyzin, Robert E. Schapire: Contextual Bandits with Linear Payoff Functions. Journal of Machine Learning Research - Proceedings Track 15: 208-214 (2011)
j8		Lihong Li, Michael L. Littman, Thomas J. Walsh, Alexander L. Strehl: Knows what it knows: a framework for self-aware learning. Machine Learning 82(3): 399-443 (2011)
c38		Yi-li Tan, Lihong Li, Yourong Wang: Dynamic Construction of Power Voronoi Diagram. ICICA (2) 2011: 660-667
c37		Miroslav Dudík, John Langford, Lihong Li: Doubly Robust Policy Evaluation and Learning. ICML 2011: 1097-1104
c36		Wei Chu, Martin Zinkevich, Lihong Li, Achint Thomas, Belle L. Tseng: Unbiased online active learning in data streams. KDD 2011: 195-203
c35		Olivier Chapelle, Lihong Li: An Empirical Evaluation of Thompson Sampling. NIPS 2011: 2249-2257
c34		Lihong Li, Wei Chu, John Langford, Xuanhui Wang: Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms. WSDM 2011: 297-306
i6		Taesup Moon, Wei Chu, Lihong Li, Zhaohui Zheng, Yi Chang: Refining Recency Search Results with User Click Feedback. CoRR abs/1103.3735 (2011)
i5		Miroslav Dudík, John Langford, Lihong Li: Doubly Robust Policy Evaluation and Learning. CoRR abs/1103.4601 (2011)
	2010
j7		John Langford, Lihong Li, Yevgeniy Vorobeychik, Jennifer Wortman: Maintaining Equilibria During Exploration in Sponsored Search Auctions. Algorithmica 58(4): 990-1021 (2010)
j6		Lihong Li, Michael L. Littman: Reducing reinforcement learning to KWIK online regression. Ann. Math. Artif. Intell. 58(3-4): 217-237 (2010)
c33		Taesup Moon, Lihong Li, Wei Chu, Ciya Liao, Zhaohui Zheng, Yi Chang: Online learning for recency search ranking using real-time user feedback. CIKM 2010: 1501-1504
c32		Lihong Li, Jinpeng Wang, Junna Jiang: Bayesian Decision Model Based on Probabilistic Rough Set with Variable Precision. ICICA (1) 2010: 32-39
c31		Lihong Li, Junna Jiang, Zhendong Li, Xufang Mu: Research and Application of Fuzzy Comprehensive Evaluation of the Optimal Weight Inverse Problem. ICICA (1) 2010: 78-84
c30		Baoxiang Liu, Ying Li, Lihong Li, Yaping Yu: An Approximate Reduction Algorithm Based on Conditional Entropy. ICICA (2) 2010: 319-325
c29		Alexander L. Strehl, John Langford, Lihong Li, Sham Kakade: Learning from Logged Implicit Exploration Data. NIPS 2010: 2217-2225
c28		Martin Zinkevich, Markus Weimer, Alexander J. Smola, Lihong Li: Parallelized Stochastic Gradient Descent. NIPS 2010: 2595-2603
c27		Lihong Li, Wei Chu, John Langford, Robert E. Schapire: A contextual-bandit approach to personalized news article recommendation. WWW 2010: 661-670
i4		Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, Robert E. Schapire: An Optimal High Probability Algorithm for the Contextual Bandit Problem. CoRR abs/1002.4058 (2010)
i3		Lihong Li, Wei Chu, John Langford, Robert E. Schapire: A Contextual-Bandit Approach to Personalized News Article Recommendation. CoRR abs/1003.0146 (2010)
i2		Lihong Li, Wei Chu, John Langford: An Unbiased, Data-Driven, Offline Evaluation Method of Contextual Bandit Algorithms. CoRR abs/1003.5956 (2010)
	2009
j5		Thomas J. Walsh, Ali Nouri, Lihong Li, Michael L. Littman: Learning and planning in environments with delayed feedback. Autonomous Agents and Multi-Agent Systems 18(1): 83-105 (2009)
j4		John Langford, Lihong Li, Tong Zhang: Sparse Online Learning via Truncated Gradient. Journal of Machine Learning Research 10: 777-801 (2009)
j3		Emma Brunskill, Bethany R. Leffler, Lihong Li, Michael L. Littman, Nicholas Roy: Provably Efficient Learning with Typed Parametric Models. Journal of Machine Learning Research 10: 1955-1988 (2009)
j2		Alexander L. Strehl, Lihong Li, Michael L. Littman: Reinforcement Learning in Finite MDPs: PAC Analysis. Journal of Machine Learning Research 10: 2413-2444 (2009)
c26		Lihong Li, Michael L. Littman, Christopher R. Mansley: Online exploration in least-squares policy iteration. AAMAS (2) 2009: 733-739
c25		Xian Wu, Lihong Li, Jian-Huang Lai, Jian Huang: A Framework of Face Tracking with Classification Using CAMShift-C and LBP. ICIG 2009: 217-222
c24		Carlos Diuk, Lihong Li, Bethany R. Leffler: The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning. ICML 2009: 32
c23		David Wingate, Carlos Diuk, Lihong Li, Matthew Taylor, Jordan Frank: Workshop summary: Results of the 2009 reinforcement learning competition. ICML 2009: 166
c22		Lihong Li, Jason D. Williams, Suhrid Balakrishnan: Reinforcement learning for dialog management using least-squares Policy iteration and fast feature selection. INTERSPEECH 2009: 2475-2478
c21		John Asmuth, Lihong Li, Michael L. Littman, Ali Nouri, David Wingate: A Bayesian Sampling Approach to Exploration in Reinforcement Learning. UAI 2009: 19-26
	2008
c20		Hongcan Yan, Dianchuan Jin, Lihong Li, Baoxiang Liu, Yanan Hao: Feature Matrix Extraction and Classification of XML Pages. APWeb Workshops 2008: 210-219
c19		Lihong Li: A worst-case comparison between temporal difference and residual gradient with linear function approximation. ICML 2008: 560-567
c18		Lihong Li, Michael L. Littman, Thomas J. Walsh: Knows what it knows: a framework for self-aware learning. ICML 2008: 568-575
c17		Ronald Parr, Lihong Li, Gavin Taylor, Christopher Painter-Wakefield, Michael L. Littman: An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning. ICML 2008: 752-759
c16		Lihong Li, Michael L. Littman: Efficient Value-Function Approximation via Online Linear Regression. ISAIM 2008
c15		John Langford, Lihong Li, Tong Zhang: Sparse Online Learning via Truncated Gradient. NIPS 2008: 905-912
c14		Chengzhi Long, Lihong Li, Weiling Wu: An Improved Scheme of SEP in Heterogeneous Wireless Sensor Networks. PACIIA (1) 2008: 655-659
c13		Chengzhi Long, Hui Chen, Lihong Li: Energy-Efficiency Cooperative Communications with Node Selection for Wireless Sensor Networks. PACIIA (2) 2008: 761-765
c12		Emma Brunskill, Bethany R. Leffler, Lihong Li, Michael L. Littman, Nicholas Roy: CORL: A Continuous-state Offset-dynamics Reinforcement Learner. UAI 2008: 53-61
i1		John Langford, Lihong Li, Tong Zhang: Sparse Online Learning via Truncated Gradient. CoRR abs/0806.4686 (2008)
	2007
j1		Lihong Li, Vadim Bulitko, Russell Greiner: Focus of Attention in Reinforcement Learning. J. UCS 13(9): 1246-1269 (2007)
c11		Thomas J. Walsh, Ali Nouri, Lihong Li, Michael L. Littman: Planning and Learning in Environments with Delayed Feedback. ECML 2007: 442-453
c10		Ronald Parr, Christopher Painter-Wakefield, Lihong Li, Michael L. Littman: Analyzing feature generation for value-function approximation. ICML 2007: 737-744
c9		Jennifer Wortman, Yevgeniy Vorobeychik, Lihong Li, John Langford: Maintaining Equilibria During Exploration in Sponsored Search Auctions. WINE 2007: 119-130
	2006
c8		Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford, Michael L. Littman: PAC model-free reinforcement learning. ICML 2006: 881-888
c7		Lihong Li, Thomas J. Walsh, Michael L. Littman: Towards a Unified Theory of State Abstraction for MDPs. ISAIM 2006
c6		Alexander L. Strehl, Lihong Li, Michael L. Littman: Incremental Model-based Learners With Formal Learning-Time Guarantees. UAI 2006
	2005
c5		Lihong Li, Michael L. Littman: Lazy Approximation for Solving Continuous Finite-Horizon MDPs. AAAI 2005: 1175-1180
c4		Chengliang Na, Tingxian Zhou, Lihong Li, Kexin Wang: AASC: adaptive avoid second-collision backoff algorithm for multihop wireless sensor networks. MASS 2005
	2004
c3		Lihong Li, Vadim Bulitko, Russell Greiner: Batch Reinforcement Learning with State Importance. ECML 2004: 566-568
	2003
c2		Ilya Levner, Vadim Bulitko, Lihong Li, Greg Lee, Russell Greiner: Towards Automated Creation of Image Interpretation Systems. Australian Conference on Artificial Intelligence 2003: 653-665
c1		Vadim Bulitko, Lihong Li, Russell Greiner, Ilya Levner: Lookahead Pathologies for Single Agent Search. IJCAI 2003: 1531-1533

Coauthor Index

Colors in the list of coauthors

Last update Mon May 20 21:22:38 2013 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page