New lower bounds of fifteen classical Ramsey numbers. - Wenlong Su; Haipeng Luo; Zhengyou Zhang; Guiqing Li (Australas. J Comb., 1999)

New lower bounds of ten classical Ramsey numbers. - Haipeng Luo; Wenlong Su; Yun-Qiu Shen (Australas. J Comb., 2001)

The properties of self-complementary graphs and new lower bounds for diagonal Ramsey numbers. - Haipeng Luo; Wenlong Su; Zhenchong Li (Australas. J Comb., 2002)

Lower bounds of Ramsey numbers based on cubic residues. - Wenlong Su; Qiao Li; Haipeng Luo; Guiqing Li (Discret. Math., 2002)

Edge colorings of the complete graph K149 and the lower bounds of three Ramsey numbers. - Guiqing Li; Wenlong Su; Haipeng Luo (Discret. Appl. Math., 2003)

New lower bounds for seven classical Ramsey numbers R(3, q). - Kang Wu; Wenlong Su; Haipeng Luo; Xiaodong Xu (Appl. Math. Lett., 2009)

The existence of balanced (υ, {3, 6}, 1) difference families. - Dianhua Wu; Minquan Cheng; Zhilin Chen; Haipeng Luo (Sci. China Inf. Sci., 2010)

A Generalization of Generalized Paley Graphs and New Lower Bounds for R(3,q). - Kang Wu; Wenlong Su; Haipeng Luo; Xiaodong Xu (Electron. J. Comb., 2010)

Upper and lower bounds for Fv(4,4;5). - Xiaodong Xu 006; Haipeng Luo; Zehui Shao (Electron. J. Comb., 2010)

Online Learning with Unknown Time Horizon. - Haipeng Luo; Robert E. Schapire (CoRR, 2013)

Towards Minimax Online Learning with Unknown Time Horizon. - Haipeng Luo; Robert E. Schapire (ICML, 2014)

A Drifting-Games Analysis for Online Learning and Applications to Boosting. - Haipeng Luo; Robert E. Schapire (NIPS, 2014)

Accelerated Parallel Optimization Methods for Large Scale Machine Learning. - Haipeng Luo; Patrick Haffner; Jean-François Paiement (CoRR, 2014)

Adaptive Resource Provisioning for the Cloud Using Online Bin Packing. - Weijia Song; Zhen Xiao; Qi Chen 009; Haipeng Luo (IEEE Trans. Computers, 2014)

Automatic Scaling of Internet Applications for Cloud Computing Services. - Zhen Xiao; Qi Chen 009; Haipeng Luo (IEEE Trans. Computers, 2014)

Achieving All with No Parameters: AdaNormalHedge. - Haipeng Luo; Robert E. Schapire (COLT, 2015)

Optimal and Adaptive Algorithms for Online Boosting. - Alina Beygelzimer; Satyen Kale; Haipeng Luo (ICML, 2015)

Online Gradient Boosting. - Alina Beygelzimer; Elad Hazan; Satyen Kale; Haipeng Luo (NIPS, 2015)

Fast Convergence of Regularized Learning in Games. - Vasilis Syrgkanis; Alekh Agarwal; Haipeng Luo; Robert E. Schapire (NIPS, 2015)

Achieving All with No Parameters: Adaptive NormalHedge. - Haipeng Luo; Robert E. Schapire (CoRR, 2015)

Variance-Reduced and Projection-Free Stochastic Optimization. - Elad Hazan; Haipeng Luo (ICML, 2016)

Efficient Second Order Online Learning by Sketching. - Haipeng Luo; Alekh Agarwal; Nicolò Cesa-Bianchi; John Langford 001 (NIPS, 2016)

Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits. - Vasilis Syrgkanis; Haipeng Luo; Akshay Krishnamurthy; Robert E. Schapire (NIPS, 2016)

Oracle-Efficient Learning and Auction Design. - Miroslav Dudík; Nika Haghtalab; Haipeng Luo; Robert E. Schapire; Vasilis Syrgkanis; Jennifer Wortman Vaughan (CoRR, 2016)

Efficient Second Order Online Learning via Sketching. - Haipeng Luo; Alekh Agarwal; Nicolò Cesa-Bianchi; John Langford 001 (CoRR, 2016)

Three-Dimensional Surface Displacement Field Associated with the 25 April 2015 Gorkha, Nepal, Earthquake: Solution from Integrated InSAR and GPS Measurements with an Extended SISTEM Approach. - Haipeng Luo; Ting Chen (Remote. Sens., 2016)

Optimal and Adaptive Online Learning - Haipeng Luo (2016)

Open Problem: First-Order Regret Bounds for Contextual Bandits. - Alekh Agarwal; Akshay Krishnamurthy; John Langford 001; Haipeng Luo; Robert E. Schapire (COLT, 2017)

Corralling a Band of Bandit Algorithms. - Alekh Agarwal; Haipeng Luo; Behnam Neyshabur; Robert E. Schapire (COLT, 2017)

Efficient Contextual Bandits in Non-stationary Worlds. - Haipeng Luo; Alekh Agarwal; John Langford 001 (CoRR, 2017)

Logistic Regression: The Importance of Being Improper. - Dylan J. Foster; Satyen Kale; Haipeng Luo; Mehryar Mohri; Karthik Sridharan (COLT, 2018)

Efficient Contextual Bandits in Non-stationary Worlds. - Haipeng Luo; Chen-Yu Wei; Alekh Agarwal; John Langford 001 (COLT, 2018)

More Adaptive Algorithms for Adversarial Bandits. - Chen-Yu Wei; Haipeng Luo (COLT, 2018)

Practical Contextual Bandits with Regression Oracles. - Dylan J. Foster; Alekh Agarwal; Miroslav Dudík; Haipeng Luo; Robert E. Schapire (ICML, 2018)

Efficient Online Portfolio with Logarithmic Regret. - Haipeng Luo; Chen-Yu Wei; Kai Zheng (NeurIPS, 2018)

Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information. - Peter Auer; Yifang Chen; Pratik Gajane; Chung-Wei Lee; Haipeng Luo; Ronald Ortner; Chen-Yu Wei (COLT, 2019)

Improved Path-length Regret Bounds for Bandits. - Sébastien Bubeck; Yuanzhi Li; Haipeng Luo; Chen-Yu Wei (COLT, 2019)

A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal and Parameter-free. - Yifang Chen; Chung-Wei Lee; Haipeng Luo; Chen-Yu Wei (COLT, 2019)

Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously. - Julian Zimmert; Haipeng Luo; Chen-Yu Wei (ICML, 2019)

Hypothesis Set Stability and Generalization. - Dylan J. Foster; Spencer Greenberg; Satyen Kale; Haipeng Luo; Mehryar Mohri; Karthik Sridharan (NeurIPS, 2019)

Model Selection for Contextual Bandits. - Dylan J. Foster; Akshay Krishnamurthy; Haipeng Luo (NeurIPS, 2019)

Equipping Experts/Bandits with Long-term Memory. - Kai Zheng 007; Haipeng Luo; Ilias Diakonikolas; Liwei Wang 001 (NeurIPS, 2019)

Learning Adversarial MDPs with Bandit Feedback and Unknown Transition. - Tiancheng Jin; Haipeng Luo (CoRR, 2019)

The Fair Contextual Multi-Armed Bandit. - Yifang Chen 004; Alex Cuellar; Haipeng Luo; Jignesh Modi; Heramb Nemlekar; Stefanos Nikolaidis (AAMAS, 2020)

Open Problem: Model Selection for Contextual Bandits. - Dylan J. Foster; Akshay Krishnamurthy; Haipeng Luo (COLT, 2020)

A Closer Look at Small-loss Bounds for Bandits with Graph Feedback. - Chung-Wei Lee; Haipeng Luo; Mengxiao Zhang (COLT, 2020)

Taking a hint: How to leverage loss predictors in contextual bandits? - Chen-Yu Wei; Haipeng Luo; Alekh Agarwal (COLT, 2020)

Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition. - Chi Jin 001; Tiancheng Jin; Haipeng Luo; Suvrit Sra; Tiancheng Yu (ICML, 2020)

Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes. - Chen-Yu Wei; Mehdi Jafarnia-Jahromi; Haipeng Luo; Hiteshi Sharma; Rahul Jain 002 (ICML, 2020)

Comparator-Adaptive Convex Bandits. - Dirk van der Hoeven; Ashok Cutkosky; Haipeng Luo (NeurIPS, 2020)

Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition. - Tiancheng Jin; Haipeng Luo (NeurIPS, 2020)

Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs. - Chung-Wei Lee; Haipeng Luo; Chen-Yu Wei; Mengxiao Zhang (NeurIPS, 2020)

Fair Contextual Multi-Armed Bandits: Theory and Experiments. - Yifang Chen 004; Alex Cuellar; Haipeng Luo; Jignesh Modi; Heramb Nemlekar; Stefanos Nikolaidis (UAI, 2020)

Linear Last-iterate Convergence for Matrix Games and Stochastic Games. - Chung-Wei Lee; Haipeng Luo; Chen-Yu Wei; Mengxiao Zhang (CoRR, 2020)

Active Online Domain Adaptation. - Yining Chen; Haipeng Luo; Tengyu Ma 001; Chicheng Zhang (CoRR, 2020)

Oracle-efficient Online Learning and Auction Design. - Miroslav Dudík; Nika Haghtalab; Haipeng Luo; Robert E. Schapire; Vasilis Syrgkanis; Jennifer Wortman Vaughan (J. ACM, 2020)

Active Online Learning with Hidden Shifting Domains. - Yining Chen; Haipeng Luo; Tengyu Ma 001; Chicheng Zhang (AISTATS, 2021)

Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation. - Chen-Yu Wei; Mehdi Jafarnia-Jahromi; Haipeng Luo; Rahul Jain 002 (AISTATS, 2021)

Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds. - Ehsan Emamjomeh-Zadeh; Chen-Yu Wei; Haipeng Luo; David Kempe 001 (ALT, 2021)

Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition. - Liyu Chen; Haipeng Luo; Chen-Yu Wei (COLT, 2021)

Impossible Tuning Made Possible: A New Expert Algorithm and Its Applications. - Liyu Chen; Haipeng Luo; Chen-Yu Wei (COLT, 2021)

Non-stationary Reinforcement Learning without Prior Knowledge: an Optimal Black-box Approach. - Chen-Yu Wei; Haipeng Luo (COLT, 2021)

Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games. - Chen-Yu Wei; Chung-Wei Lee; Mengxiao Zhang; Haipeng Luo (COLT, 2021)

Linear Last-iterate Convergence in Constrained Saddle-point Optimization. - Chen-Yu Wei; Chung-Wei Lee; Mengxiao Zhang; Haipeng Luo (ICLR, 2021)

Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case. - Liyu Chen; Haipeng Luo (ICML, 2021)

Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously. - Chung-Wei Lee; Haipeng Luo; Chen-Yu Wei; Mengxiao Zhang; Xiaojin Zhang 002 (ICML, 2021)

Multi-Armed Bandits and Reinforcement Learning: Advancing Decision Making in E-Commerce and Beyond. - Daniel R. Jiang; Haipeng Luo; Chu Wang; Yingfei Wang (KDD, 2021)

Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path. - Liyu Chen; Mehdi Jafarnia-Jahromi; Rahul Jain 002; Haipeng Luo (NeurIPS, 2021)

The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition. - Tiancheng Jin; Longbo Huang; Haipeng Luo (NeurIPS, 2021)

Last-iterate Convergence in Extensive-Form Games. - Chung-Wei Lee; Christian Kroer; Haipeng Luo (NeurIPS, 2021)

Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses. - Haipeng Luo; Chen-Yu Wei; Chung-Wei Lee (NeurIPS, 2021)

Online Learning for Stochastic Shortest Path Model via Posterior Sampling. - Mehdi Jafarnia-Jahromi; Liyu Chen; Rahul Jain 002; Haipeng Luo (CoRR, 2021)

Policy Optimization for Stochastic Shortest Path. - Liyu Chen; Haipeng Luo; Aviv Rosenberg 002 (COLT, 2022)

Adaptive Bandit Convex Optimization with Heterogeneous Curvature. - Haipeng Luo; Mengxiao Zhang; Peng Zhao 006 (COLT, 2022)

Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits. - Haipeng Luo; Mengxiao Zhang; Peng Zhao 006; Zhi-Hua Zhou (COLT, 2022)

Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP. - Liyu Chen; Rahul Jain 002; Haipeng Luo (ICML, 2022)

Learning Infinite-horizon Average-reward Markov Decision Process with Constraints. - Liyu Chen; Rahul Jain 002; Haipeng Luo (ICML, 2022)

Kernelized Multiplicative Weights for 0/1-Polyhedral Games: Bridging the Gap Between Learning in Extensive-Form and Normal-Form Games. - Gabriele Farina; Chung-Wei Lee; Haipeng Luo; Christian Kroer (ICML, 2022)

No-Regret Learning in Time-Varying Zero-Sum Games. - Mengxiao Zhang; Peng Zhao 006; Haipeng Luo; Zhi-Hua Zhou (ICML, 2022)

Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback. - Yan Dai 002; Haipeng Luo; Liyu Chen (NeurIPS, 2022)

Uncoupled Learning Dynamics with O(log T) Swap Regret in Multiplayer Games. - Ioannis Anagnostides; Gabriele Farina; Christian Kroer; Chung-Wei Lee; Haipeng Luo; Tuomas Sandholm (NeurIPS, 2022)

Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments. - Liyu Chen; Haipeng Luo (NeurIPS, 2022)

Near-Optimal No-Regret Learning Dynamics for General Convex Games. - Gabriele Farina; Ioannis Anagnostides; Haipeng Luo; Chung-Wei Lee; Christian Kroer; Tuomas Sandholm (NeurIPS, 2022)

Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback. - Tiancheng Jin; Tal Lancewicki; Haipeng Luo; Yishay Mansour; Aviv Rosenberg 002 (NeurIPS, 2022)

Learning Infinite-Horizon Average-Reward Markov Decision Processes with Constraints. - Liyu Chen; Rahul Jain 002; Haipeng Luo (CoRR, 2022)

Uncoupled Learning Dynamics with O(log T) Swap Regret in Multiplayer Games. - Ioannis Anagnostides; Gabriele Farina; Christian Kroer; Chung-Wei Lee; Haipeng Luo; Tuomas Sandholm (CoRR, 2022)

Near-Optimal No-Regret Learning for General Convex Games. - Gabriele Farina; Ioannis Anagnostides; Haipeng Luo; Chung-Wei Lee; Christian Kroer; Tuomas Sandholm (CoRR, 2022)

Clairvoyant Regret Minimization: Equivalence with Nemirovski's Conceptual Prox Method and Extension to General Convex Games. - Gabriele Farina; Christian Kroer; Chung-Wei Lee; Haipeng Luo (CoRR, 2022)

No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution. - Mengxiao Zhang; Shi Chen; Haipeng Luo; Yingfei Wang (AISTATS, 2023)

Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphs. - Haipeng Luo; Hanghang Tong; Mengxiao Zhang; Yuheng Zhang (ALT, 2023)

Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval? - Wenhao Wu; Haipeng Luo; Bo Fang 003; Jingdong Wang 001; Wanli Ouyang (CVPR, 2023)

Bidirectional Cross-Modal Knowledge Exploration for Video Recognition with Pre-trained Vision-Language Models. - Wenhao Wu; Xiaohan Wang; Haipeng Luo; Jingdong Wang 001; Yi Yang 001; Wanli Ouyang (CVPR, 2023)

Refined Regret for Adversarial MDPs with Linear Function Approximation. - Yan Dai 002; Haipeng Luo; Chen-Yu Wei; Julian Zimmert (ICML, 2023)

2nd Workshop on Multi-Armed Bandits and Reinforcement Learning: Advancing Decision Making in E-Commerce and Beyond. - Chu Wang; Yingfei Wang; Haipeng Luo; Daniel R. Jiang; Jinghai He; Zeyu Zheng (KDD, 2023)

Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback. - Yang Cai 001; Haipeng Luo; Chen-Yu Wei; Weiqiang Zheng (NeurIPS, 2023)

Regret Matching+: (In)Stability and Fast Convergence in Games. - Gabriele Farina; Julien Grand-Clément; Christian Kroer; Chung-Wei Lee; Haipeng Luo (NeurIPS, 2023)

Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms. - Tiancheng Jin; Junyan Liu; Haipeng Luo (NeurIPS, 2023)

No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions. - Tiancheng Jin; Junyan Liu; Chloé Rouyer; William Chang; Chen-Yu Wei; Haipeng Luo (NeurIPS, 2023)

Practical Contextual Bandits with Feedback Graphs. - Mengxiao Zhang; Yuheng Zhang; Olga Vrousgou; Haipeng Luo; Paul Mineiro (NeurIPS, 2023)

Posterior sampling-based online learning for the stochastic shortest path model. - Mehdi Jafarnia-Jahromi; Liyu Chen; Rahul Jain 002; Haipeng Luo (UAI, 2023)

Average-Constrained Policy Optimization. - Akhil Agnihotri; Rahul Jain 002; Haipeng Luo (CoRR, 2023)

Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games. - Yang Cai 001; Haipeng Luo; Chen-Yu Wei; Weiqiang Zheng (CoRR, 2023)

WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct. - Haipeng Luo; Qingfeng Sun; Can Xu; Pu Zhao 004; Jianguang Lou; Chongyang Tao; Xiubo Geng; Qingwei Lin; Shifeng Chen; Dongmei Zhang 001 (CoRR, 2023)

Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games. - Yang Cai 001; Haipeng Luo; Chen-Yu Wei; Weiqiang Zheng (AISTATS, 2024)

Online Learning in Contextual Second-Price Pay-Per-Click Auctions. - Mengxiao Zhang; Haipeng Luo (AISTATS, 2024)

ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints. - Akhil Agnihotri; Rahul Jain 002; Haipeng Luo (ICML, 2024)

Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback. - Asaf Cassel; Haipeng Luo; Aviv Rosenberg 002; Dmitry Sotnikov (ICML, 2024)

Efficient Contextual Bandits with Uninformed Feedback Graphs. - Mengxiao Zhang; Yuheng Zhang; Haipeng Luo; Paul Mineiro (ICML, 2024)

On Tractable Φ-Equilibria in Non-Concave Games. - Yang Cai 001; Constantinos Daskalakis; Haipeng Luo; Chen-Yu Wei; Weiqiang Zheng (NeurIPS, 2024)

Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms. - Yang Cai 001; Gabriele Farina; Julien Grand-Clément; Christian Kroer; Chung-Wei Lee; Haipeng Luo; Weiqiang Zheng (NeurIPS, 2024)

Optimal Multiclass U-Calibration Error and Beyond. - Haipeng Luo; Spandan Senapati; Vatsal Sharan (NeurIPS, 2024)

WizardArena: Post-training Large Language Models via Simulated Offline Chatbot Arena. - Haipeng Luo; Qingfeng Sun; Can Xu; Pu Zhao 004; Qingwei Lin; Jian-Guang Lou; Shifeng Chen; Yansong Tang; Weizhu Chen (NeurIPS, 2024)

Contextual Multinomial Logit Bandits with General Value Functions. - Mengxiao Zhang; Haipeng Luo (NeurIPS, 2024)

No-Regret Learning for Fair Multi-Agent Social Welfare Optimization. - Mengxiao Zhang; Ramiro Deo-Campo Vuong; Haipeng Luo (NeurIPS, 2024)

Provably Efficient Interactive-Grounded Learning with Personalized Reward. - Mengxiao Zhang; Yuheng Zhang; Haipeng Luo; Paul Mineiro (NeurIPS, 2024)

Tractable Local Equilibria in Non-Concave Games. - Yang Cai 001; Constantinos Daskalakis; Haipeng Luo; Chen-Yu Wei; Weiqiang Zheng (CoRR, 2024)

Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback. - Asaf B. Cassel; Haipeng Luo; Aviv Rosenberg 002; Dmitry Sotnikov (CoRR, 2024)

Arena Learning: Build Data Flywheel for LLMs Post-training via Simulated Chatbot Arena. - Haipeng Luo; Qingfeng Sun; Can Xu; Pu Zhao 004; Qingwei Lin; Jianguang Lou; Shifeng Chen; Yansong Tang; Weizhu Chen (CoRR, 2024)

Data for "Slow Rupture in a Fluid-rich Fault Zone Initiated the 2024 Mw 7.5 Noto Earthquake". - Zhang-Feng Ma; Hongyu Zeng; Haipeng Luo; Zemin Liu; Yu Jiang; Yosuke Aoki; Weitao Wang; Yuji Itoh; Mingzhe Lyu; Yan Cui; Sang-Ho Yun; Emma Hill; et al. (Zenodo, 2024)

Alternating Regret for Online Convex Optimization. - Soumita Hait; Ping Li; Haipeng Luo; Mengxiao Zhang (COLT, 2025)

Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback. - Shinji Ito; Haipeng Luo; Taira Tsuchiya; Yue Wu (COLT, 2025)

Corrupted Learning Dynamics in Games. - Taira Tsuchiya; Shinji Ito; Haipeng Luo (COLT, 2025)

Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games. - Yang Cai 001; Gabriele Farina; Julien Grand-Clément; Christian Kroer; Chung-Wei Lee; Haipeng Luo; Weiqiang Zheng (ICLR, 2025)

WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct. - Haipeng Luo; Qingfeng Sun; Can Xu; Pu Zhao 004; Jian-Guang Lou; Chongyang Tao; Xiubo Geng; Qingwei Lin; Shifeng Chen; Yansong Tang; Dongmei Zhang 001 (ICLR, 2025)

S²HGC: An End-to-End Spectral-Spatial Hypergraph Convolutional Network for Unsupervised Hyperspectral Band Selection. - Kaixiong Wu; Mingwei Wang 003; Haipeng Luo; Maolin Chen; Yujie Xu; Wei Liu 099 (IEEE Trans. Geosci. Remote. Sens., 2025)

Contextual Linear Bandits with Delay as Payoff. - Mengxiao Zhang; Yingfei Wang; Haipeng Luo (CoRR, 2025)

Simultaneous Swap Regret Minimization via KL-Calibration. - Haipeng Luo; Spandan Senapati; Vatsal Sharan (CoRR, 2025)

On Separation Between Best-Iterate, Random-Iterate, and Last-Iterate Convergence of Learning in Games. - Yang Cai 001; Gabriele Farina; Julien Grand-Clément; Christian Kroer; Chung-Wei Lee; Haipeng Luo; Weiqiang Zheng (CoRR, 2025)

Group Distributionally Robust Optimization with Flexible Sample Queries. - Haomin Bai; Dingzhi Yu; Shuai Li; Haipeng Luo; Lijun Zhang (CoRR, 2025)

Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought. - Ao Liu; Botong Zhou; Can Xu; Chayse Zhou; Chenchen Zhang; Chengcheng Xu; Chenhao Wang; Decheng Wu; Dengpeng Wu; Dian Jiao; Dong Du; Dong Wang; et al. (CoRR, 2025)

Comparator-Adaptive Φ-Regret: Improved Bounds, Simpler Algorithms, and Applications to Games. - Soumita Hait; Ping Li; Haipeng Luo; Mengxiao Zhang (CoRR, 2025)

Improved Regret and Contextual Linear Extension for Pandora's Box and Prophet Inequality. - Junyan Liu; Ziyun Chen; Kun Wang; Haipeng Luo; Lillian J. Ratliff (CoRR, 2025)

Improved Bounds for Swap Multicalibration and Swap Omniprediction. - Haipeng Luo; Spandan Senapati; Vatsal Sharan (CoRR, 2025)

From Average-Iterate to Last-Iterate Convergence in Games: A Reduction and Its Applications. - Yang Cai 001; Haipeng Luo; Chen-Yu Wei; Weiqiang Zheng (CoRR, 2025)

Reinforcement Learning from Adversarial Preferences in Tabular MDPs. - Taira Tsuchiya; Shinji Ito; Haipeng Luo (CoRR, 2025)

Cap4Video++: Enhancing Video Understanding With Auxiliary Captions. - Wenhao Wu; Xiaohan Wang; Haipeng Luo; Jingdong Wang 001; Yi Yang 001; Wanli Ouyang (IEEE Trans. Pattern Anal. Mach. Intell., 2025)