← Authors

Haipeng Luo

88 papers · 2014–2025 · 9 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (11) 🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (15) πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (17) 🧭 Keyword Pioneer 🏠 Conference Loyalist (33) πŸ† Keyword Champion (32) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ”¬ Deep Specialist (36) 🀝 Dynamic Duo (24) πŸ”₯ Unstoppable (12) ⚑ Prolific Year (11) ❓ The Questioner (2) πŸ’Ž Century Club (88) πŸ—ƒοΈ Keyword Collector (66)

Conferences

NIPS (33) COLT (22) ICML (18) AISTATS (5) ICLR (3) ALT (2) CVPR (2) UAI (2) IJCAI (1)

Top co-authors

Chen-Yu Wei (24) Mengxiao Zhang (18) Chung-Wei Lee (15) Liyu Chen (10) Christian Kroer (7) Rahul Jain (7) Alekh Agarwal (7) Tiancheng Jin (6) Gabriele Farina (6) Satyen Kale (5)

Keywords

regret bound (48) online learning (32) contextual bandit (14) multi-armed bandit (13) markov decision process (8) game theory (8) bandit feedback (7) online mirror descent (7) stochastic shortest path (7) dynamic regret (7) adversarial learning (6) multi-agent system (6) stochastic optimization (5) nash equilibrium (5) adversarial bandit (5) reinforcement learning (5) online algorithm (4) no-regret learning (4) linear bandit (4) policy optimization (4)

Papers

Corrupted Learning Dynamics in Games COLT 2025
Contextual Linear Bandits with Delay as Payoff ICML 2025
Alternating Regret for Online Convex Optimization COLT 2025
Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback COLT 2025
Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games ICLR 2025
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct ICLR 2025
Provably Efficient Interactive-Grounded Learning with Personalized Reward NIPS 2024
WizardArena: Post-training Large Language Models via Simulated Offline Chatbot Arena NIPS 2024
Efficient Contextual Bandits with Uninformed Feedback Graphs ICML 2024
Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback ICML 2024
No-Regret Learning for Fair Multi-Agent Social Welfare Optimization NIPS 2024
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms NIPS 2024
Contextual Multinomial Logit Bandits with General Value Functions NIPS 2024
Optimal Multiclass U-Calibration Error and Beyond NIPS 2024
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games AISTATS 2024
Online Learning in Contextual Second-Price Pay-Per-Click Auctions AISTATS 2024
ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints ICML 2024
On Tractable $\Phi$-Equilibria in Non-Concave Games NIPS 2024
Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval? CVPR 2023
Posterior sampling-based online learning for the stochastic shortest path model UAI 2023
Practical Contextual Bandits with Feedback Graphs NIPS 2023
Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms NIPS 2023
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback NIPS 2023
No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions NIPS 2023
Regret Matching+: (In)Stability and Fast Convergence in Games NIPS 2023
No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution AISTATS 2023
Refined Regret for Adversarial MDPs with Linear Function Approximation ICML 2023
Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphs ALT 2023
Bidirectional Cross-Modal Knowledge Exploration for Video Recognition With Pre-Trained Vision-Language Models CVPR 2023
Uncoupled Learning Dynamics with $O(\log T)$ Swap Regret in Multiplayer Games NIPS 2022
Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP ICML 2022
Learning Infinite-horizon Average-reward Markov Decision Process with Constraints ICML 2022
Near-Optimal No-Regret Learning Dynamics for General Convex Games NIPS 2022
Kernelized Multiplicative Weights for 0/1-Polyhedral Games: Bridging the Gap Between Learning in Extensive-Form and Normal-Form Games ICML 2022
No-Regret Learning in Time-Varying Zero-Sum Games ICML 2022
Policy Optimization for Stochastic Shortest Path COLT 2022
Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits COLT 2022
Adaptive Bandit Convex Optimization with Heterogeneous Curvature COLT 2022
Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments NIPS 2022
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback NIPS 2022
Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback NIPS 2022
Active Online Learning with Hidden Shifting Domains AISTATS 2021
Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path NIPS 2021
Last-iterate Convergence in Extensive-Form Games NIPS 2021
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition NIPS 2021
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses NIPS 2021
Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation AISTATS 2021
Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds ALT 2021
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition COLT 2021
Impossible Tuning Made Possible: A New Expert Algorithm and Its Applications COLT 2021
Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games COLT 2021
Non-stationary Reinforcement Learning without Prior Knowledge: an Optimal Black-box Approach COLT 2021
Linear Last-iterate Convergence in Constrained Saddle-point Optimization ICLR 2021
Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case ICML 2021
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously ICML 2021
Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs NIPS 2020
Open Problem: Model Selection for Contextual Bandits COLT 2020
Comparator-Adaptive Convex Bandits NIPS 2020
Taking a hint: How to leverage loss predictors in contextual bandits? COLT 2020
A Closer Look at Small-loss Bounds for Bandits with Graph Feedback COLT 2020
Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition ICML 2020
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020
Fair Contextual Multi-Armed Bandits: Theory and Experiments UAI 2020
Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition NIPS 2020
Improved Path-length Regret Bounds for Bandits COLT 2019
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously ICML 2019
Model Selection for Contextual Bandits NIPS 2019
A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal and Parameter-free COLT 2019
Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information COLT 2019
Equipping Experts/Bandits with Long-term Memory NIPS 2019
Hypothesis Set Stability and Generalization NIPS 2019
Efficient Online Portfolio with Logarithmic Regret NIPS 2018
Practical Contextual Bandits with Regression Oracles ICML 2018
Efficient Contextual Bandits in Non-stationary Worlds COLT 2018
More Adaptive Algorithms for Adversarial Bandits COLT 2018
Logistic Regression: The Importance of Being Improper COLT 2018
Corralling a Band of Bandit Algorithms COLT 2017
Open Problem: First-Order Regret Bounds for Contextual Bandits COLT 2017
Efficient Second Order Online Learning by Sketching NIPS 2016
Optimal and Adaptive Algorithms for Online Boosting IJCAI 2016
Variance-Reduced and Projection-Free Stochastic Optimization ICML 2016
Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits NIPS 2016
Optimal and Adaptive Algorithms for Online Boosting ICML 2015
Achieving All with No Parameters: AdaNormalHedge COLT 2015
Fast Convergence of Regularized Learning in Games NIPS 2015
Online Gradient Boosting NIPS 2015
Towards Minimax Online Learning with Unknown Time Horizon ICML 2014
A Drifting-Games Analysis for Online Learning and Applications to Boosting NIPS 2014