Lihong Li - Concepedia

Author

Lihong Li

Stony Brook University ORCID

Also Known As

L Li, L. Li, Li, Lihong, Li-Hong Li, Li-hong Li, LiHong Li, Lihong Li, Lihong Li -, Li‐Hong Li, Li⁃hong LI

217

Publications

6.8K

Citations

H-Index

181

Concepts

All Affiliations

Stony Brook University City University of New York College of Staten Island Microsoft (United States)State University of New York

About

Lihong Li is an author at Stony Brook University specializing in engineering, machine learning, and artificial intelligence.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	32	60	4.1K
2	Health Sciences	10	10	667
3	Language Studies	8	8	861
4	Education	6	6	492
5	Arts	2	2	48

Lihong Li

Publications

6.5K

Citations

H-Index

Page 1

	Year	Citations
Contextual bandits with linear Payoff functions Wei Chu, Lihong Li, Lev Reyzin,	2011	577
PAC model-free reinforcement learning Alexander L. Strehl, Lihong Li, Eric Wiewiora, Artificial IntelligenceModel-free LearningEngineeringMachine LearningData Science	2006	409
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits Alekh Agarwal, Daniel Hsu, Satyen Kale, arXiv (Cornell University)	2014	313
Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access Bhuwan Dhingra, Lihong Li, Xiujun Li, Artificial IntelligenceDialogue AgentsEngineeringSpoken Dialog SystemMulti-agent Learning	2017	299
Towards a Unified Theory of State Abstraction for MDPs. Lihong Li, Thomas J. Walsh, Michael L. Littman	2006	265
Texture Feature Analysis for Computer-Aided Diagnosis on Pulmonary Nodules Fangfang Han, Huafeng Wang, Guopeng Zhang, Journal of Digital Imaging Image AnalysisMachine VisionMedical ImagingEngineeringPattern Recognition	2014	264
Contextual Bandit Algorithms with Supervised Learning Guarantees Alina Beygelzimer, John Langford, Lihong Li, arXiv (Cornell University) Artificial IntelligenceEngineeringMachine LearningAlgorithmic LearningContextual Bandit Algorithms	2010	203
Reinforcement Learning in Finite MDPs: PAC Analysis Alexander L. Strehl, Lihong Li, Michael L. Littman Journal of Machine Learning Research Mathematical ProgrammingNear-optimal BehaviorMachine LearningEngineeringStochastic Optimization	2009	199
Deep Reinforcement Learning with a Natural Language Action Space Ji He, Jianshu Chen, Xiaodong He, Natural Language ProcessingArtificial IntelligenceApplied LinguisticsNatural LanguageEngineering	2016	173
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning Ronald Parr, Lihong Li, Gavin Taylor, Artificial IntelligenceEngineeringMachine LearningValue Function ApproximationFeature Selection	2008	157

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