Lihong Li

发表

An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning

Lihong Li, Michael L. Littman, Gavin Taylor, 2008, ICML '08.

Randomized Exploration in Generalized Linear Bandits

Craig Boutilier, Csaba Szepesvári, Manzil Zaheer, 2019, AISTATS.

Toward Minimax Off-policy Value Estimation

Lihong Li, Csaba Szepesvári, Rémi Munos, 2015, AISTATS.

Recurrent Reinforcement Learning: A Hybrid Approach pdf

Jianfeng Gao, Xiujun Li, Li Deng, 2015, ArXiv.

A Novel Benchmark Methodology and Data Repository for Real-life Reinforcement Learning

Ronald E. Parr, M. Littman, Lihong Li, 2009 .

Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits

John Langford, Lihong Li, Robert E. Schapire, 2014, ICML.

Learning from Logged Implicit Exploration Data

Lihong Li, Sham M. Kakade, Alexander L. Strehl, 2010, NIPS.

Parallelized Stochastic Gradient Descent

Alexander J. Smola, Lihong Li, Markus Weimer, 2010, NIPS.

Combating Deep Reinforcement Learning's Sisyphean Curse with Intrinsic Fear

Zachary Chase Lipton, Lihong Li, Jianfeng Gao, 2016, 1611.01211.

PAC model-free reinforcement learning

Lihong Li, Michael L. Littman, Alexander L. Strehl, 2006, ICML.

Efficient Exploration for Dialogue Policy Learning with BBQ Networks & Replay Buffer Spiking

Zachary Chase Lipton, Lihong Li, Xiujun Li, 2016 .

Contextual Bandits with Global Constraints and Objective pdf

Nikhil R. Devanur, Lihong Li, Shipra Agrawal, 2015, ArXiv.

An Empirical Evaluation of Thompson Sampling

Lihong Li, Olivier Chapelle, O. Chapelle, 2011, NIPS.

Sparse Online Learning via Truncated Gradient

John Langford, Lihong Li, Tong Zhang, 2008, NIPS.

Doubly Robust Policy Evaluation and Optimization pdf

John Langford, Dumitru Erhan, Miroslav Dudík, 2014, ArXiv.

Knows what it knows: a framework for self-aware learning

Thomas J. Walsh, Lihong Li, Michael L. Littman, 2008, ICML '08.

Doubly Robust Policy Evaluation and Learning

John Langford, Miroslav Dudík, Lihong Li, 2011, ICML.

Towards a Unified Theory of State Abstraction for MDPs

Thomas J. Walsh, Lihong Li, Michael L. Littman, 2006, AI&M.

Doubly Robust Off-policy Value Evaluation for Reinforcement Learning

Nan Jiang, Lihong Li, Lihong Li, 2015, ICML.

A contextual-bandit approach to personalized news article recommendation pdf

Wei Chu, Lihong Li, John Langford, 2010, WWW '10.

Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear pdf

Jianfeng Gao, Li Deng, Lihong Li, 2016, ArXiv.

Combating Deep Reinforcement Learning ’ s Sisyphean Curse with Reinforcement Learning

Zachary Chase Lipton, Lihong Li, Jianfeng Gao, 2017 .

Contextual Bandit Algorithms with Supervised Learning Guarantees

John Langford, Lihong Li, Robert E. Schapire, 2010, AISTATS.

A Bayesian Sampling Approach to Exploration in Reinforcement Learning pdf

Lihong Li, Michael L. Littman, David Wingate, 2009, UAI.

Unbiased online active learning in data streams

Lihong Li, Belle L. Tseng, Martin Zinkevich, 2011, KDD.

Online Evaluation for Information Retrieval

Filip Radlinski, Katja Hofmann, Lihong Li, 2016, Found. Trends Inf. Retr..

Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms

Wei Chu, John Langford, Lihong Li, 2010, WSDM '11.

Maintaining Equilibria During Exploration in Sponsored Search Auctions

John Langford, Yevgeniy Vorobeychik, Lihong Li, 2007, WINE.

Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation

Qiang Liu, Lihong Li, Dengyong Zhou, 2018, NeurIPS.

PAC-inspired Option Discovery in Lifelong Reinforcement Learning

Lihong Li, Emma Brunskill, Lihong Li, 2014, ICML.

Generalized Thompson Sampling for Contextual Bandits pdf

Lihong Li, Lihong Li, 2013, ArXiv.

Cloud control: voluntary admission control for intranet traffic management

John Langford, Lihong Li, R. Preston McAfee, 2012, Inf. Syst. E Bus. Manag..

Sample Complexity of Multi-task Reinforcement Learning pdf

Lihong Li, Emma Brunskill, Lihong Li, 2013, UAI.

Reducing reinforcement learning to KWIK online regression

Lihong Li, Michael L. Littman, M. Littman, 2010, Annals of Mathematics and Artificial Intelligence.

Stochastic Variance Reduction Methods for Policy Evaluation

Lihong Li, Lin Xiao, Jianshu Chen, 2017, ICML.

Exploration in Least-Squares Policy Iteration

M. Littman, Lihong Li, C. Mansley, 2008 .

A unifying framework for computational reinforcement learning theory

Michael L. Littman, Lihong Li, M. Littman, 2009 .

BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems

Jianfeng Gao, Xiujun Li, Li Deng, 2016, AAAI.

Counterfactual Estimation and Optimization of Click Metrics in Search Engines: A Case Study

Lihong Li, Jim Kleban, Ankur Gupta, 2015, WWW.

Provable Optimal Algorithms for Generalized Linear Contextual Bandits

Lihong Li, Yu Lu, Dengyong Zhou, 2017, ArXiv.

Click-based Hot Fixes for Underperforming Torso Queries

M. de Rijke, Maarten de Rijke, Lihong Li, 2016, SIGIR.

The Online Coupon-Collector Problem and Its Application to Lifelong Reinforcement Learning

Lihong Li, Emma Brunskill, Lihong Li, 2015 .

Escaping the Gravitational Pull of Softmax

Csaba Szepesvári, Dale Schuurmans, Bo Dai, 2020, NeurIPS.

PAC-MDP Reinforcement Learning with Bayesian Priors

Michael L. Littman, David Wingate, Ali Nouri, 2009 .

Doubly Robust Policy Evaluation and Optimization 1

D. Erhan, J. Langford, Lihong Li, 2015 .

Action Space Defined by Natural Language

Lihong Li, Jianfeng Gao, Xiaodong He, 2016 .

Lazy Approximation : A New Approach for Solving Continuous Finite-Horizon MDPs

M. Littman, Lihong Li, 2005 .

INFINITE-HORIZON REINFORCEMENT LEARNING

Lihong Li, Dengyong Zhou, Qiang Liu, 2020 .

Exploiting User Preference for Online Learning in Web Content Optimization Systems

Yi Chang, Anlei Dong, Bo Long, 2014, TIST.

NeuralUCB: Contextual Bandits with Neural Network-Based Exploration

Quanquan Gu, Lihong Li, Dongruo Zhou, 2019 .

Doubly Robust Off-policy Evaluation for Reinforcement Learning pdf

Nan Jiang, Lihong Li, Lihong Li, 2015, ArXiv.

An Unbiased, Data-Driven, Offline Evaluation Method of Contextual Bandit Algorithms pdf

Wei Chu, John Langford, Lihong Li, 2010, ArXiv.

An Optimal High Probability Algorithm for the Contextual Bandit Problem pdf

John Langford, Lihong Li, Robert E. Schapire, 2010, ArXiv.

Efficient Dialogue Policy Learning with BBQ-Networks

Zachary Chase Lipton, Lihong Li, Xiujun Li, 2016, 1608.05081.

Bandits with Generalized Linear Models

Wei Chu, John Langford, Lihong Li, 2012, ICML On-line Trading of Exploration and Exploitation.

A Reinforcement Learning Approach to Estimating Long-term Treatment Effects

Lihong Li, Ziyang Tang, Stephanie S. Zhang, 2022, ArXiv.

Off-Policy Evaluation via the Regularized Lagrangian

Lihong Li, D. Schuurmans, Ofir Nachum, 2020, NeurIPS.

Offline Policy Optimization in RL with Variance Regularizaton

Samin Yeasar Arnob, Doina Precup, Lihong Li, 2022, ArXiv.

Sample Complexity Bounds of Exploration

Lihong Li, Lihong Li, 2012, Reinforcement Learning.

Reinforcement Learning in Finite MDPs: PAC Analysis

Lihong Li, Michael L. Littman, Alexander L. Strehl, 2009, J. Mach. Learn. Res..

Incremental Model-based Learners With Formal Learning-Time Guarantees pdf

Lihong Li, Michael L. Littman, Alexander L. Strehl, 2006, UAI.

Understanding Domain Randomization for Sim-to-real Transfer

Lihong Li, Chi Jin, Liwei Wang, 2021, ICLR.

Deep Reinforcement Learning with a Natural Language Action Space

Jianfeng Gao, Mari Ostendorf, Li Deng, 2015, ACL.

Neural Logic Machines pdf

Chong Wang, Lihong Li, Denny Zhou, 2019, ICLR.

Policy Certificates: Towards Accountable Reinforcement Learning pdf

Lihong Li, Wei Wei, Christoph Dann, 2018, ICML.

Data Poisoning Attacks in Contextual Bandits pdf

Lihong Li, Xiaojin Zhu, Yuzhe Ma, 2018, GameSec.

Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders pdf

Ali Mousavi, Nathan Kallus, Lihong Li, 2020, AISTATS.

Learning and planning in environments with delayed feedback

Thomas J. Walsh, Lihong Li, Michael L. Littman, 2009, Autonomous Agents and Multi-Agent Systems.

Neuro-Symbolic Program Synthesis pdf

Lihong Li, Pushmeet Kohli, Emilio Parisotto, 2016, ICLR.

An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives

Nikhil R. Devanur, Lihong Li, Shipra Agrawal, 2015, COLT.

Contextual Bandits with Linear Payoff Functions

Wei Chu, Lihong Li, Robert E. Schapire, 2011, AISTATS.

Neural Approaches to Conversational AI

Jianfeng Gao, Lihong Li, Michel Galley, 2018, ACL.

Linear-Time Estimators for Propensity Scores

Alexander J. Smola, Lihong Li, Deepak Agarwal, 2011, AISTATS.

Neural Contextual Bandits with UCB-based Exploration

Quanquan Gu, Lihong Li, Dongruo Zhou, 2019, ICML.

Neural Contextual Bandits with Upper Confidence Bound-Based Exploration pdf

Quanquan Gu, Lihong Li, Dongruo Zhou, 2019, ArXiv.

Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access

Jianfeng Gao, Xiujun Li, Li Deng, 2016, ACL.

End-to-End Task-Completion Neural Dialogue Systems

Jianfeng Gao, Xiujun Li, Asli Celikyilmaz, 2017, IJCNLP.

Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads

Jianfeng Gao, Mari Ostendorf, Li Deng, 2016, EMNLP.

Composite Task-Completion Dialogue Policy Learning via Hierarchical Deep Reinforcement Learning

Kam-Fai Wong, Sungjin Lee, Jianfeng Gao, 2017, EMNLP.

A User Simulator for Task-Completion Dialogues pdf

Jianfeng Gao, Xiujun Li, Lihong Li, 2016, ArXiv.

Neural Approaches to Conversational AI: Question Answering, Task-oriented Dialogues and Social Chatbots

Jianfeng Gao, Michel Galley, Lihong Li, 2019 .

AlgaeDICE: Policy Gradient from Arbitrary Experience pdf

Ilya Kostrikov, Bo Dai, Lihong Li, 2019, ArXiv.

Toward Predicting the Outcome of an A/B Experiment for Search Relevance

Lihong Li, Jinyoung Kim, Imed Zitouni, 2015, WSDM.

CoinDICE: Off-Policy Confidence Interval Estimation pdf

Csaba Szepesvári, Bo Dai, Lihong Li, 2020, NeurIPS.

GenDICE: Generalized Offline Estimation of Stationary Values pdf

Bo Dai, Dale Schuurmans, Ruiyi Zhang, 2020, ICLR.

Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation pdf

Qiang Liu, Yihao Feng, Dengyong Zhou, 2019, ICLR.

DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections

Bo Dai, Ofir Nachum, Yinlam Chow, 2019, NeurIPS.

An unbiased offline evaluation of contextual bandit algorithms with generalized linear models

Wei Chu, John Langford, Lihong Li, 2011 .

SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation

Le Song, Zhen Liu, Bo Dai, 2017, ICML.

Analyzing feature generation for value-function approximation

Lihong Li, Michael L. Littman, Ronald Parr, 2007, ICML '07.

Deep Reinforcement Learning with an Action Space Defined by Natural Language

Jianfeng Gao, Mari Ostendorf, Xiaodong He, 2015 .

Boosting the Actor with Dual Critic pdf

Le Song, Bo Dai, Lihong Li, 2017, ICLR.

Planning and Learning in Environments with Delayed Feedback

Thomas J. Walsh, Lihong Li, Michael L. Littman, 2007, ECML.

On the Optimality of Batch Policy Optimization Algorithms

Tor Lattimore, Dale Schuurmans, Chenjun Xiao, 2021, ICML.

A Kernel Loss for Solving the Bellman Equation

Qiang Liu, Yihao Feng, Lihong Li, 2019, NeurIPS.

Lazy Approximation for Solving Continuous Finite-Horizon MDPs

Lihong Li, Michael L. Littman, M. Littman, 2005, AAAI.

Batch Stationary Distribution Estimation pdf

Bo Dai, Dale Schuurmans, Junfeng Wen, 2020, ICML.

Investigation of Language Understanding Impact for Reinforcement Learning Based Dialogue Systems pdf

Jianfeng Gao, Xiujun Li, Lihong Li, 2017, ArXiv.

Efficient Dialogue Policy Learning with BBQ-Networks

Zachary Chase Lipton, Lihong Li, Xiujun Li, 2016, 1608.05081.

Efficient Exploration for Dialog Policy Learning with Deep BBQ Networks \& Replay Buffer Spiking pdf

Jianfeng Gao, Xiujun Li, Li Deng, 2016, ArXiv.

Neural Thompson Sampling pdf

Quanquan Gu, Dongruo Zhou, Lihong Li, 2020, ICLR.

Near-optimal Representation Learning for Linear Bandits and Linear RL

Xiaoyu Chen, Liwei Wang, Chi Jin, 2021, ICML.

Scalable Bilinear π Learning Using State and Action Features

Lihong Li, Mengdi Wang, Yichen Chen, 2018, ICML 2018.

Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL pdf

Lihong Li, Xiaoyu Chen, Liwei Wang, 2020, ICLR.

Maintaining Equilibria During Exploration in Sponsored Search Auctions

John Langford, Yevgeniy Vorobeychik, Lihong Li, 2010, Algorithmica.

Understanding Domain Randomization for Sim-to-real Transfer

Lihong Li, Chi Jin, Liwei Wang, 2021, ICLR.

A worst-case comparison between temporal difference and residual gradient with linear function approximation

Lihong Li, Lihong Li, 2008, ICML '08.

Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits

John Langford, Dumitru Erhan, Miroslav Dudík, 2012, UAI.

Subgoal Discovery for Hierarchical Dialogue Policy Learning pdf

Chong Wang, Jianfeng Gao, Xiujun Li, 2018, EMNLP.

Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes

Chong Wang, Li Deng, Lihong Li, 2017, NIPS.

On the Prior Sensitivity of Thompson Sampling pdf

Lihong Li, Che-Yu Liu, Lihong Li, 2015, ALT.

A Map of Bandits for E-commerce pdf

Lihong Li, Yi Liu, Lihong Li, 2021, ArXiv.

Active Learning with Oracle Epiphany

Lihong Li, Xiaojin Zhu, Tzu-Kuo Huang, 2016, NIPS.

Adversarial Attacks on Stochastic Bandits

Lihong Li, Xiaojin Zhu, Yuzhe Ma, 2018, NeurIPS.

Composite Task-Completion Dialogue System via Hierarchical Deep Reinforcement Learning pdf

Kam-Fai Wong, Sungjin Lee, Jianfeng Gao, 2017, ArXiv.

Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning pdf

Qiang Liu, Ali Mousavi, Lihong Li, 2020, ICLR.

Doubly Robust Off-policy Evaluation for Reinforcement Learning

Lihong Li, Nan Jiang, 2015, ArXiv.

Deep Reinforcement Learning with a Combinatorial Action Space for Predicting and Tracking Popular Discussion Threads pdf

Jianfeng Gao, Mari Ostendorf, Li Deng, 2016, ArXiv.

Deep Reinforcement Learning with an Unbounded Action Space pdf

Jianfeng Gao, Mari Ostendorf, Li Deng, 2015, ArXiv.

A perspective on off-policy evaluation in reinforcement learning

Lihong Li, 2019, Frontiers of Computer Science.

Joint relevance and freshness learning from clickthroughs for news search

Evgeniy Gabrilovich, Lihong Li, Yi Chang, 2012, WWW.

Smoothed Dual Embedding Control pdf

Le Song, Bo Dai, Lihong Li, 2017, ArXiv.

Online exploration in least-squares policy iteration

Lihong Li, Michael L. Littman, Christopher R. Mansley, 2009, AAMAS.

The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning

Lihong Li, Bethany R. Leffler, Carlos Diuk, 2009, ICML '09.

Evaluation of Explore-Exploit Policies in Multi-result Ranking Systems pdf

Lihong Li, Dragomir Yankov, Pavel Berkhin, 2015, ArXiv.

An unbiased offline evaluation of contextual bandit algorithms with generalized linear models

J. Langford, Lihong Li, Wei Chu, 2011 .

Sparse Online Learning via Truncated Gradient

J. Langford, Tong Zhang, Lihong Li, 2008, NIPS.

The Online Discovery Problem and Its Application to Lifelong Reinforcement Learning pdf

Lihong Li, Emma Brunskill, Lihong Li, 2015, ArXiv.

DualDICE: Efficient Estimation of Off-Policy Stationary Distribution Corrections

Bo Dai, Ofir Nachum, Yinlam Chow, 2019 .

Neural Contextual Bandits with UCB-based Exploration

Lihong Li, Quanquan Gu, Dongruo Zhou, 2019, ICML.

Offline Evaluation and Optimization for Interactive Systems

Lihong Li, Lihong Li, 2015, WSDM.

On Minimax Optimal Offline Policy Evaluation pdf

Lihong Li, Csaba Szepesvári, Rémi Munos, 2014, ArXiv.

Refining Recency Search Results with User Click Feedback pdf

Wei Chu, Lihong Li, Zhaohui Zheng, 2011, ArXiv.