Haipeng Luo

ORCID

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 149

Top Venues

Publications

Haipeng Luo, Spandan Senapati, Vatsal Sharan
Optimal Multiclass U-Calibration Error and Beyond. CoRR (2024)
Yang Cai, Constantinos Daskalakis, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
Tractable Local Equilibria in Non-Concave Games. CoRR (2024)
Mengxiao Zhang, Haipeng Luo
Online Learning in Contextual Second-Price Pay-Per-Click Auctions. AISTATS (2024)
Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro
Provably Efficient Interactive-Grounded Learning with Personalized Reward. CoRR (2024)
Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro
Efficient Contextual Bandits with Uninformed Feedback Graphs. CoRR (2024)
Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Qingwei Lin, Jianguang Lou, Shifeng Chen, Yansong Tang, Weizhu Chen
Arena Learning: Build Data Flywheel for LLMs Post-training via Simulated Chatbot Arena. CoRR (2024)
Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games. AISTATS (2024)
Mengxiao Zhang, Ramiro Deo-Campo Vuong, Haipeng Luo
No-Regret Learning for Fair Multi-Agent Social Welfare Optimization. CoRR (2024)
Mengxiao Zhang, Haipeng Luo
Contextual Multinomial Logit Bandits with General Value Functions. CoRR (2024)
Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games. CoRR (2024)
Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms. CoRR (2024)
Asaf Cassel, Haipeng Luo, Aviv Rosenberg, Dmitry Sotnikov
Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback. CoRR (2024)
Wenhao Wu, Xiaohan Wang, Haipeng Luo, Jingdong Wang, Yi Yang, Wanli Ouyang
Bidirectional Cross-Modal Knowledge Exploration for Video Recognition with Pre-trained Vision-Language Models. CoRR (2023)
Haipeng Luo, Hanghang Tong, Mengxiao Zhang, Yuheng Zhang
Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphs. ALT (2023)
Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo
Regret Matching+: (In)Stability and Fast Convergence in Games. CoRR (2023)
Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo
Regret Matching+: (In)Stability and Fast Convergence in Games. NeurIPS (2023)
Yan Dai, Haipeng Luo, Chen-Yu Wei, Julian Zimmert
Refined Regret for Adversarial MDPs with Linear Function Approximation. ICML (2023)
Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo
No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions. NeurIPS (2023)
Wenhao Wu, Haipeng Luo, Bo Fang, Jingdong Wang, Wanli Ouyang
Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval? CVPR (2023)
Tiancheng Jin, Junyan Liu, Haipeng Luo
Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms. NeurIPS (2023)
Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng
Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games. CoRR (2023)
Mehdi Jafarnia-Jahromi, Liyu Chen, Rahul Jain, Haipeng Luo
Posterior sampling-based online learning for the stochastic shortest path model. UAI (2023)
Wenhao Wu, Haipeng Luo, Bo Fang, Jingdong Wang, Wanli Ouyang
Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval? CoRR (2023)
Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games. CoRR (2023)
Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Jianguang Lou, Chongyang Tao, Xiubo Geng, Qingwei Lin, Shifeng Chen, Dongmei Zhang
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct. CoRR (2023)
Yan Dai, Haipeng Luo, Chen-Yu Wei, Julian Zimmert
Refined Regret for Adversarial MDPs with Linear Function Approximation. CoRR (2023)
Tiancheng Jin, Junyan Liu, Haipeng Luo
Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms. CoRR (2023)
Akhil Agnihotri, Rahul Jain, Haipeng Luo
Average-Constrained Policy Optimization. CoRR (2023)
Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo
No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions. CoRR (2023)
Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback. NeurIPS (2023)
Chu Wang, Yingfei Wang, Haipeng Luo, Daniel Jiang, Jinghai He, Zeyu Zheng
2nd Workshop on Multi-Armed Bandits and Reinforcement Learning: Advancing Decision Making in E-Commerce and Beyond. KDD (2023)
Mengxiao Zhang, Shi Chen, Haipeng Luo, Yingfei Wang
No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution. AISTATS (2023)
Mengxiao Zhang, Yuheng Zhang, Olga Vrousgou, Haipeng Luo, Paul Mineiro
Practical Contextual Bandits with Feedback Graphs. NeurIPS (2023)
Wenhao Wu, Xiaohan Wang, Haipeng Luo, Jingdong Wang, Yi Yang, Wanli Ouyang
Bidirectional Cross-Modal Knowledge Exploration for Video Recognition with Pre-trained Vision-Language Models. CVPR (2023)
Mengxiao Zhang, Haipeng Luo
Online Learning in Contextual Second-Price Pay-Per-Click Auctions. CoRR (2023)
Haipeng Luo, Hanghang Tong, Mengxiao Zhang, Yuheng Zhang
Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphs. CoRR (2022)
Gabriele Farina, Ioannis Anagnostides, Haipeng Luo, Chung-Wei Lee, Christian Kroer, Tuomas Sandholm
Near-Optimal No-Regret Learning Dynamics for General Convex Games. NeurIPS (2022)
Haipeng Luo, Mengxiao Zhang, Peng Zhao, Zhi-Hua Zhou
Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits. COLT (2022)
Ioannis Anagnostides, Gabriele Farina, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Tuomas Sandholm
Uncoupled Learning Dynamics with O(log T) Swap Regret in Multiplayer Games. CoRR (2022)
Liyu Chen, Rahul Jain, Haipeng Luo
Learning Infinite-horizon Average-reward Markov Decision Process with Constraints. ICML (2022)
Gabriele Farina, Christian Kroer, Chung-Wei Lee, Haipeng Luo
Clairvoyant Regret Minimization: Equivalence with Nemirovski's Conceptual Prox Method and Extension to General Convex Games. CoRR (2022)
Mengxiao Zhang, Peng Zhao, Haipeng Luo, Zhi-Hua Zhou
No-Regret Learning in Time-Varying Zero-Sum Games. CoRR (2022)
Gabriele Farina, Chung-Wei Lee, Haipeng Luo, Christian Kroer
Kernelized Multiplicative Weights for 0/1-Polyhedral Games: Bridging the Gap Between Learning in Extensive-Form and Normal-Form Games. ICML (2022)
Ioannis Anagnostides, Gabriele Farina, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Tuomas Sandholm
Swap Regret in Multiplayer Games. NeurIPS (2022)
Liyu Chen, Haipeng Luo, Aviv Rosenberg
Policy Optimization for Stochastic Shortest Path. CoRR (2022)
Gabriele Farina, Ioannis Anagnostides, Haipeng Luo, Chung-Wei Lee, Christian Kroer, Tuomas Sandholm
Near-Optimal No-Regret Learning for General Convex Games. CoRR (2022)
Liyu Chen, Rahul Jain, Haipeng Luo
Learning Infinite-Horizon Average-Reward Markov Decision Processes with Constraints. CoRR (2022)
Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback. CoRR (2022)
Liyu Chen, Haipeng Luo, Aviv Rosenberg
Policy Optimization for Stochastic Shortest Path. COLT (2022)
Haipeng Luo, Mengxiao Zhang, Peng Zhao
Adaptive Bandit Convex Optimization with Heterogeneous Curvature. COLT (2022)
Liyu Chen, Rahul Jain, Haipeng Luo
Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP. ICML (2022)
Yan Dai, Haipeng Luo, Liyu Chen
Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback. CoRR (2022)
Mengxiao Zhang, Shi Chen, Haipeng Luo, Yingfei Wang
No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution. CoRR (2022)
Haipeng Luo, Mengxiao Zhang, Peng Zhao
Adaptive Bandit Convex Optimization with Heterogeneous Curvature. CoRR (2022)
Yan Dai, Haipeng Luo, Liyu Chen
Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback. NeurIPS (2022)
Liyu Chen, Haipeng Luo
Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments. CoRR (2022)
Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback. NeurIPS (2022)
Haipeng Luo, Mengxiao Zhang, Peng Zhao, Zhi-Hua Zhou
Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits. CoRR (2022)
Liyu Chen, Haipeng Luo
Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments. NeurIPS (2022)
Gabriele Farina, Chung-Wei Lee, Haipeng Luo, Christian Kroer
Kernelized Multiplicative Weights for 0/1-Polyhedral Games: Bridging the Gap Between Learning in Extensive-Form and Normal-Form Games. CoRR (2022)
Mengxiao Zhang, Peng Zhao, Haipeng Luo, Zhi-Hua Zhou
No-Regret Learning in Time-Varying Zero-Sum Games. ICML (2022)
Liyu Chen, Rahul Jain, Haipeng Luo
Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP. CoRR (2021)
Liyu Chen, Haipeng Luo
Finding the Stochastic Shortest Path with Low Regret: The Adversarial Cost and Unknown Transition Case. CoRR (2021)
Haipeng Luo, Chen-Yu Wei, Chung-Wei Lee
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses. NeurIPS (2021)
Chen-Yu Wei, Haipeng Luo
Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach. CoRR (2021)
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously. ICML (2021)
Tiancheng Jin, Longbo Huang, Haipeng Luo
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition. NeurIPS (2021)
Daniel Jiang, Haipeng Luo, Chu Wang, Yingfei Wang
Multi-Armed Bandits and Reinforcement Learning: Advancing Decision Making in E-Commerce and Beyond. KDD (2021)
Mehdi Jafarnia-Jahromi, Liyu Chen, Rahul Jain, Haipeng Luo
Online Learning for Stochastic Shortest Path Model via Posterior Sampling. CoRR (2021)
Haipeng Luo, Chen-Yu Wei, Chung-Wei Lee
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses. CoRR (2021)
Liyu Chen, Mehdi Jafarnia-Jahromi, Rahul Jain, Haipeng Luo
Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path. NeurIPS (2021)
Ehsan Emamjomeh-Zadeh, Chen-Yu Wei, Haipeng Luo, David Kempe
Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds. ALT (2021)
Liyu Chen, Haipeng Luo, Chen-Yu Wei
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition. COLT (2021)
Liyu Chen, Haipeng Luo, Chen-Yu Wei
Impossible Tuning Made Possible: A New Expert Algorithm and Its Applications. COLT (2021)
Liyu Chen, Haipeng Luo
Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case. ICML (2021)
Chung-Wei Lee, Christian Kroer, Haipeng Luo
Last-iterate Convergence in Extensive-Form Games. CoRR (2021)
Liyu Chen, Haipeng Luo, Chen-Yu Wei
Impossible Tuning Made Possible: A New Expert Algorithm and Its Applications. CoRR (2021)
Chen-Yu Wei, Chung-Wei Lee, Mengxiao Zhang, Haipeng Luo
Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games. CoRR (2021)
Tiancheng Jin, Longbo Huang, Haipeng Luo
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition. CoRR (2021)
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo, Rahul Jain
Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation. AISTATS (2021)
Chen-Yu Wei, Chung-Wei Lee, Mengxiao Zhang, Haipeng Luo
Linear Last-iterate Convergence in Constrained Saddle-point Optimization. ICLR (2021)
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously. CoRR (2021)
Chung-Wei Lee, Christian Kroer, Haipeng Luo
Last-iterate Convergence in Extensive-Form Games. NeurIPS (2021)
Chen-Yu Wei, Chung-Wei Lee, Mengxiao Zhang, Haipeng Luo
Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games. COLT (2021)
Yining Chen, Haipeng Luo, Tengyu Ma, Chicheng Zhang
Active Online Learning with Hidden Shifting Domains. AISTATS (2021)
Liyu Chen, Mehdi Jafarnia-Jahromi, Rahul Jain, Haipeng Luo
Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path. CoRR (2021)
Chen-Yu Wei, Haipeng Luo
Non-stationary Reinforcement Learning without Prior Knowledge: an Optimal Black-box Approach. COLT (2021)
Chen-Yu Wei, Haipeng Luo, Alekh Agarwal
Taking a hint: How to leverage loss predictors in contextual bandits? CoRR (2020)
Chi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, Tiancheng Yu
Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition. ICML (2020)
Miroslav Dudíte, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
Oracle-efficient Online Learning and Auction Design. J. ACM 67 (5) (2020)
Tiancheng Jin, Haipeng Luo
Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition. NeurIPS (2020)
Chung-Wei Lee, Haipeng Luo, Mengxiao Zhang
A Closer Look at Small-loss Bounds for Bandits with Graph Feedback. CoRR (2020)
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo, Rahul Jain
Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation. CoRR (2020)
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo, Hiteshi Sharma, Rahul Jain
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes. ICML (2020)
Ehsan Emamjomeh-Zadeh, Chen-Yu Wei, Haipeng Luo, David Kempe
Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds. CoRR (2020)
Chung-Wei Lee, Haipeng Luo, Mengxiao Zhang
A Closer Look at Small-loss Bounds for Bandits with Graph Feedback. COLT (2020)
Chen-Yu Wei, Haipeng Luo, Alekh Agarwal
Taking a hint: How to leverage loss predictors in contextual bandits? COLT (2020)
Mehdi Jafarnia-Jahromi, Chen-Yu Wei, Rahul Jain, Haipeng Luo
A Model-free Learning Algorithm for Infinite-horizon Average-reward MDPs with Near-optimal Regret. CoRR (2020)
Dylan J. Foster, Akshay Krishnamurthy, Haipeng Luo
Open Problem: Model Selection for Contextual Bandits. CoRR (2020)
Tiancheng Jin, Haipeng Luo
Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Haipeng Luo