Lihong Li

Publication Activity (10 Years)

Years Active: 2003-2022
Publications (10 Years): 95

Top Venues

CoRR

ICML

NeurIPS

ICLR

Publications

Ziyang Tang, Yiheng Duan, Steven Zhu, Stephanie Zhang, Lihong Li
Estimating Long-term Effects from Experimental Data. RecSys (2022)
Ziyang Tang, Yiheng Duan, Stephanie Zhang, Lihong Li
A Reinforcement Learning Approach to Estimating Long-term Treatment Effects. CoRR (2022)
Xiaoyu Chen, Jiachen Hu, Chi Jin, Lihong Li, Liwei Wang
Understanding Domain Randomization for Sim-to-real Transfer. ICLR (2022)
Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvári, Dale Schuurmans
On the Optimality of Batch Policy Optimization Algorithms. ICML (2021)
Weitong Zhang, Dongruo Zhou, Lihong Li, Quanquan Gu
Neural Thompson Sampling. ICLR (2021)
Andrew Bennett, Nathan Kallus, Lihong Li, Ali Mousavi
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders. AISTATS (2021)
Chenjun Xiao, Yifan Wu, Tor Lattimore, Bo Dai, Jincheng Mei, Lihong Li, Csaba Szepesvári, Dale Schuurmans
On the Optimality of Batch Policy Optimization Algorithms. CoRR (2021)
Mengjiao Yang, Ofir Nachum, Bo Dai, Lihong Li, Dale Schuurmans
Off-Policy Evaluation via the Regularized Lagrangian. NeurIPS (2020)
Ge Liu, Rui Wu, Heng-Tze Cheng, Jing Wang, Jayden Ooi, Lihong Li, Ang Li, Wai Lok Sibon Li, Craig Boutilier, Ed Chi
Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing. CoRR (2020)
Ruiyi Zhang, Bo Dai, Lihong Li, Dale Schuurmans
GenDICE: Generalized Offline Estimation of Stationary Values. ICLR (2020)
Mengjiao Yang, Ofir Nachum, Bo Dai, Lihong Li, Dale Schuurmans
Off-Policy Evaluation via the Regularized Lagrangian. CoRR (2020)
Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans
CoinDICE: Off-Policy Confidence Interval Estimation. NeurIPS (2020)
Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier
Randomized Exploration in Generalized Linear Bandits. AISTATS (2020)
Ali Mousavi, Lihong Li, Qiang Liu, Denny Zhou
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning. ICLR (2020)
Ruiyi Zhang, Bo Dai, Lihong Li, Dale Schuurmans
GenDICE: Generalized Offline Estimation of Stationary Values. CoRR (2020)
Weitong Zhang, Dongruo Zhou, Lihong Li, Quanquan Gu
Neural Thompson Sampling. CoRR (2020)
Junfeng Wen, Bo Dai, Lihong Li, Dale Schuurmans
Batch Stationary Distribution Estimation. ICML (2020)
Dongruo Zhou, Lihong Li, Quanquan Gu
Neural Contextual Bandits with UCB-based Exploration. ICML (2020)
Ziyang Tang, Yihao Feng, Lihong Li, Dengyong Zhou, Qiang Liu
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation. ICLR (2020)
Ali Mousavi, Lihong Li, Qiang Liu, Denny Zhou
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning. CoRR (2020)
Andrew Bennett, Nathan Kallus, Lihong Li, Ali Mousavi
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders. CoRR (2020)
Junfeng Wen, Bo Dai, Lihong Li, Dale Schuurmans
Batch Stationary Distribution Estimation. CoRR (2020)
Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans
CoinDICE: Off-Policy Confidence Interval Estimation. CoRR (2020)
Jincheng Mei, Chenjun Xiao, Bo Dai, Lihong Li, Csaba Szepesvári, Dale Schuurmans
Escaping the Gravitational Pull of Softmax. NeurIPS (2020)
Jianfeng Gao, Michel Galley, Lihong Li
Neural Approaches to Conversational AI. Found. Trends Inf. Retr. 13 (2-3) (2019)
Yihao Feng, Lihong Li, Qiang Liu
A Kernel Loss for Solving the Bellman Equation. CoRR (2019)
Ziyang Tang, Yihao Feng, Lihong Li, Dengyong Zhou, Qiang Liu
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation. CoRR (2019)
Dongruo Zhou, Lihong Li, Quanquan Gu
Neural Contextual Bandits with Upper Confidence Bound-Based Exploration. CoRR (2019)
Ofir Nachum, Bo Dai, Ilya Kostrikov, Yinlam Chow, Lihong Li, Dale Schuurmans
AlgaeDICE: Policy Gradient from Arbitrary Experience. CoRR (2019)
Yihao Feng, Lihong Li, Qiang Liu
A Kernel Loss for Solving the Bellman Equation. NeurIPS (2019)
Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections. NeurIPS (2019)
Honghua Dong, Jiayuan Mao, Tian Lin, Chong Wang, Lihong Li, Denny Zhou
Neural Logic Machines. CoRR (2019)
Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections. CoRR (2019)
Honghua Dong, Jiayuan Mao, Tian Lin, Chong Wang, Lihong Li, Denny Zhou
Neural Logic Machines. ICLR (Poster) (2019)
Lihong Li
A perspective on off-policy evaluation in reinforcement learning. Frontiers Comput. Sci. 13 (5) (2019)
Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier
Randomized Exploration in Generalized Linear Bandits. CoRR (2019)
Christoph Dann, Lihong Li, Wei Wei, Emma Brunskill
Policy Certificates: Towards Accountable Reinforcement Learning. ICML (2019)
Kwang-Sung Jun, Lihong Li, Yuzhe Ma, Xiaojin Zhu
Adversarial Attacks on Stochastic Bandits. CoRR (2018)
Zachary C. Lipton, Xiujun Li, Jianfeng Gao, Lihong Li, Faisal Ahmed, Li Deng
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems. AAAI (2018)
Yuzhe Ma, Kwang-Sung Jun, Lihong Li, Xiaojin Zhu
Data Poisoning Attacks in Contextual Bandits. GameSec (2018)
Bo Dai, Albert Shaw, Niao He, Lihong Li, Le Song
Boosting the Actor with Dual Critic. ICLR (Poster) (2018)
Da Tang, Xiujun Li, Jianfeng Gao, Chong Wang, Lihong Li, Tony Jebara
Subgoal Discovery for Hierarchical Dialogue Policy Learning. EMNLP (2018)
Da Tang, Xiujun Li, Jianfeng Gao, Chong Wang, Lihong Li, Tony Jebara
Subgoal Discovery for Hierarchical Dialogue Policy Learning. CoRR (2018)
Jianfeng Gao, Michel Galley, Lihong Li
Neural Approaches to Conversational AI. ACL (5) (2018)
Jianfeng Gao, Michel Galley, Lihong Li
Neural Approaches to Conversational AI. SIGIR (2018)
Kwang-Sung Jun, Lihong Li, Yuzhe Ma, Xiaojin (Jerry) Zhu
Adversarial Attacks on Stochastic Bandits. NeurIPS (2018)
Yuzhe Ma, Kwang-Sung Jun, Lihong Li, Xiaojin Zhu
Data Poisoning Attacks in Contextual Bandits. CoRR (2018)
Yichen Chen, Lihong Li, Mengdi Wang
Scalable Bilinear Learning Using State and Action Features. ICML (2018)
Christoph Dann, Lihong Li, Wei Wei, Emma Brunskill
Policy Certificates: Towards Accountable Reinforcement Learning. CoRR (2018)
Yichen Chen, Lihong Li, Mengdi Wang
Scalable Bilinear π Learning Using State and Action Features. CoRR (2018)
Qiang Liu, Lihong Li, Ziyang Tang, Dengyong Zhou
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation. CoRR (2018)
Jianfeng Gao, Michel Galley, Lihong Li
Neural Approaches to Conversational AI. CoRR (2018)
Qiang Liu, Lihong Li, Ziyang Tang, Dengyong Zhou
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation. NeurIPS (2018)
Bo Dai, Albert Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation. ICML (2018)
Baolin Peng, Xiujun Li, Lihong Li, Jianfeng Gao, Asli Celikyilmaz, Sungjin Lee, Kam-Fai Wong
Composite Task-Completion Dialogue Policy Learning via Hierarchical Deep Reinforcement Learning. EMNLP (2017)
Bo Dai, Albert Shaw, Lihong Li, Lin Xiao, Niao He, Jianshu Chen, Le Song
Smoothed Dual Embedding Control. CoRR (2017)
Simon S. Du, Jianshu Chen, Lihong Li, Lin Xiao, Dengyong Zhou
Stochastic Variance Reduction Methods for Policy Evaluation. CoRR (2017)
Lihong Li, Yu Lu, Dengyong Zhou
Provable Optimal Algorithms for Generalized Linear Contextual Bandits. CoRR (2017)
Jianshu Chen, Chong Wang, Lin Xiao, Ji He, Lihong Li, Li Deng
Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes. NIPS (2017)
Bhuwan Dhingra, Lihong Li, Xiujun Li, Jianfeng Gao, Yun-Nung Chen, Faisal Ahmed, Li Deng
Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access. ACL (1) (2017)
Simon S. Du, Jianshu Chen, Lihong Li, Lin Xiao, Dengyong Zhou
Stochastic Variance Reduction Methods for Policy Evaluation. ICML (2017)
Asli Celikyilmaz, Li Deng, Lihong Li, Chong Wang
Scaffolding Networks for Teaching and Learning to Comprehend. CoRR (2017)
Xiujun Li, Yun-Nung Chen, Lihong Li, Jianfeng Gao, Asli Celikyilmaz
Investigation of Language Understanding Impact for Reinforcement Learning Based Dialogue Systems. CoRR (2017)
Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh, Lihong Li, Dengyong Zhou, Pushmeet Kohli
Neuro-Symbolic Program Synthesis. ICLR (Poster) (2017)
Xiujun Li, Yun-Nung Chen, Lihong Li, Jianfeng Gao, Asli Celikyilmaz
End-to-End Task-Completion Neural Dialogue Systems. IJCNLP(1) (2017)
Lihong Li, Yu Lu, Dengyong Zhou
Provably Optimal Algorithms for Generalized Linear Contextual Bandits. ICML (2017)
Baolin Peng, Xiujun Li, Lihong Li, Jianfeng Gao, Asli Celikyilmaz, Sungjin Lee, Kam-Fai Wong
Composite Task-Completion Dialogue System via Hierarchical Deep Reinforcement Learning. CoRR (2017)
Bo Dai, Albert Shaw, Niao He, Lihong Li, Le Song
Boosting the Actor with Dual Critic. CoRR (2017)
Xiujun Li, Yun-Nung Chen, Lihong Li, Jianfeng Gao
End-to-End Task-Completion Neural Dialogue Systems. CoRR (2017)
Zachary C. Lipton, Jianfeng Gao, Lihong Li, Xiujun Li, Faisal Ahmed, Li Deng
Efficient Exploration for Dialog Policy Learning with Deep BBQ Networks \& Replay Buffer Spiking. CoRR (2016)
Katja Hofmann, Lihong Li, Filip Radlinski
Online Evaluation for Information Retrieval. Found. Trends Inf. Retr. 10 (1) (2016)
Ji He, Mari Ostendorf, Xiaodong He, Jianshu Chen, Jianfeng Gao, Lihong Li, Li Deng
Deep Reinforcement Learning with a Combinatorial Action Space for Predicting and Tracking Popular Discussion Threads. CoRR (2016)
Nan Jiang, Lihong Li
Doubly Robust Off-policy Value Evaluation for Reinforcement Learning. ICML (2016)
Xiujun Li, Zachary C. Lipton, Bhuwan Dhingra, Lihong Li, Jianfeng Gao, Yun-Nung Chen
A User Simulator for Task-Completion Dialogues. CoRR (2016)
Bhuwan Dhingra, Lihong Li, Xiujun Li, Jianfeng Gao, Yun-Nung Chen, Faisal Ahmed, Li Deng
End-to-End Reinforcement Learning of Dialogue Agents for Information Access. CoRR (2016)
Masrour Zoghi, Tomás Tunys, Lihong Li, Damien Jose, Junyan Chen, Chun Ming Chin, Maarten de Rijke
Click-based Hot Fixes for Underperforming Torso Queries. SIGIR (2016)
Zachary C. Lipton, Jianfeng Gao, Lihong Li, Jianshu Chen, Li Deng
Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear. CoRR (2016)
Tzu-Kuo Huang, Lihong Li, Ara Vartanian, Saleema Amershi, Xiaojin Zhu
Active Learning with Oracle Epiphany. NIPS (2016)
Che-Yu Liu, Lihong Li
On the Prior Sensitivity of Thompson Sampling. ALT (2016)
Ji He, Mari Ostendorf, Xiaodong He, Jianshu Chen, Jianfeng Gao, Lihong Li, Li Deng
Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads. EMNLP (2016)
Shipra Agrawal, Nikhil R. Devanur, Lihong Li
An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives. COLT (2016)
Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh, Lihong Li, Dengyong Zhou, Pushmeet Kohli
Neuro-Symbolic Program Synthesis. CoRR (2016)
Ji He, Jianshu Chen, Xiaodong He, Jianfeng Gao, Lihong Li, Li Deng, Mari Ostendorf
Deep Reinforcement Learning with a Natural Language Action Space. ACL (1) (2016)
Lihong Li
Offline Evaluation and Optimization for Interactive Systems. WSDM (2015)
Che-Yu Liu, Lihong Li
On the Prior Sensitivity of Thompson Sampling. CoRR (2015)
Emma Brunskill, Lihong Li
The Online Discovery Problem and Its Application to Lifelong Reinforcement Learning. CoRR (2015)
Dragomir Yankov, Pavel Berkhin, Lihong Li
Evaluation of Explore-Exploit Policies in Multi-result Ranking Systems. CoRR (2015)
Lihong Li, Rémi Munos, Csaba Szepesvári
Toward Minimax Off-policy Value Estimation. AISTATS (2015)
Lihong Li, Jinyoung Kim, Imed Zitouni
Toward Predicting the Outcome of an A/B Experiment for Search Relevance. WSDM (2015)
Shipra Agrawal, Nikhil R. Devanur, Lihong Li
Contextual Bandits with Global Constraints and Objective. CoRR (2015)
Nan Jiang, Lihong Li
Doubly Robust Off-policy Evaluation for Reinforcement Learning. CoRR (2015)
Ji He, Jianshu Chen, Xiaodong He, Jianfeng Gao, Lihong Li, Li Deng, Mari Ostendorf
Deep Reinforcement Learning with an Unbounded Action Space. CoRR (2015)
Lihong Li, Shunbao Chen, Jim Kleban, Ankur Gupta
Counterfactual Estimation and Optimization of Click Metrics in Search Engines: A Case Study. WWW (Companion Volume) (2015)
Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
Doubly Robust Policy Evaluation and Optimization. CoRR (2015)
Xiujun Li, Lihong Li, Jianfeng Gao, Xiaodong He, Jianshu Chen, Li Deng, Ji He
Recurrent Reinforcement Learning: A Hybrid Approach. CoRR (2015)
Lihong Li, He He, Jason D. Williams
Temporal supervised learning for inferring a dialog policy from example conversations. SLT (2014)
Lihong Li, Rémi Munos, Csaba Szepesvári
On Minimax Optimal Offline Policy Evaluation. CoRR (2014)
Jiang Bian, Bo Long, Lihong Li, Taesup Moon, Anlei Dong, Yi Chang
Exploiting User Preference for Online Learning in Web Content Optimization Systems. ACM Trans. Intell. Syst. Technol. 5 (2) (2014)
Emma Brunskill, Lihong Li
PAC-inspired Option Discovery in Lifelong Reinforcement Learning. ICML (2014)
Lihong Li, Shunbao Chen, Jim Kleban, Ankur Gupta
Counterfactual Estimation and Optimization of Click Metrics for Search Engines. CoRR (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Lihong Li