2025 "regret minimization" Papers

28 papers found

Adapting to Stochastic and Adversarial Losses in Episodic MDPs with Aggregate Bandit Feedback

Shinji Ito, Kevin Jamieson, Haipeng Luo et al.

NEURIPS 2025posterarXiv:2510.17103
1
citations

Almost Optimal Batch-Regret Tradeoff for Batch Linear Contextual Bandits

Zihan Zhang, Xiangyang Ji, Yuan Zhou

ICLR 2025posterarXiv:2110.08057
10
citations

An Improved Algorithm for Adversarial Linear Contextual Bandits via Reduction

Tim van Erven, Jack Mayo, Julia Olkhovskaya et al.

NEURIPS 2025posterarXiv:2508.11931

An Online Learning Theory of Trading-Volume Maximization

Tommaso Cesari, Roberto Colomboni

ICLR 2025poster
3
citations

Causal LLM Routing: End-to-End Regret Minimization from Observational Data

Asterios Tsiourvas, Wei Sun, Georgia Perakis

NEURIPS 2025posterarXiv:2505.16037
5
citations

Comparator-Adaptive $\Phi$-Regret: Improved Bounds, Simpler Algorithms, and Applications to Games

Soumita Hait, Ping Li, Haipeng Luo et al.

NEURIPS 2025spotlight

Comparing Uniform Price and Discriminatory Multi-Unit Auctions through Regret Minimization

Marius Potfer, Vianney Perchet

NEURIPS 2025posterarXiv:2510.19591

Contextual Dynamic Pricing with Heterogeneous Buyers

Thodoris Lykouris, Sloan Nietert, Princewill Okoroafor et al.

NEURIPS 2025posterarXiv:2512.09513

Feature-Based Online Bilateral Trade

Solenne Gaucher, Martino Bernasconi, Matteo Castiglioni et al.

ICLR 2025posterarXiv:2405.18183
3
citations

Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment

Aadirupa Saha, Pierre Gaillard

ICLR 2025poster
1
citations

Improved Regret and Contextual Linear Extension for Pandora's Box and Prophet Inequality

Junyan Liu, Ziyun Chen, Kun Wang et al.

NEURIPS 2025posterarXiv:2505.18828

Learning from Imperfect Human Feedback: A Tale from Corruption-Robust Dueling

Yuwei Cheng, Fan Yao, Xuefeng Liu et al.

ICLR 2025posterarXiv:2405.11204
2
citations

Learning to price with resource constraints: from full information to machine-learned prices

Ruicheng Ao, Jiashuo Jiang, David Simchi-Levi

NEURIPS 2025posterarXiv:2501.14155
3
citations

Linear Bandits with Memory

Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi

ICLR 2025posterarXiv:2302.08345
3
citations

Markov Persuasion Processes: Learning to Persuade From Scratch

Francesco Bacchiocchi, Francesco Emanuele Stradi, Matteo Castiglioni et al.

NEURIPS 2025posterarXiv:2402.03077
9
citations

Near-Optimal Regret-Queue Length Tradeoff in Online Learning for Two-Sided Markets

Zixian Yang, Sushil Varma, Lei Ying

NEURIPS 2025posterarXiv:2510.14097

Neural Combinatorial Clustered Bandits for Recommendation Systems

Baran Atalar, Carlee Joe-Wong

AAAI 2025paperarXiv:2410.14586
3
citations

No-Regret Online Autobidding Algorithms in First-price Auctions

Yilin LI, Yuan Deng, Wei Tang et al.

NEURIPS 2025posterarXiv:2510.16869
1
citations

Online Learning in the Repeated Mediated Newsvendor Problem

Nataša Bolić, Tom Cesari, Roberto Colomboni et al.

NEURIPS 2025poster

On the Universal Near Optimality of Hedge in Combinatorial Settings

Zhiyuan Fan, Arnab Maiti, Lillian Ratliff et al.

NEURIPS 2025spotlightarXiv:2510.17099

Optimal Regret of Bandits under Differential Privacy

Achraf Azize, Yulian Wu, Junya Honda et al.

NEURIPS 2025poster

Provably Efficient RL under Episode-Wise Safety in Constrained MDPs with Linear Function Approximation

Toshinori Kitamura, Arnob Ghosh, Tadashi Kozuno et al.

NEURIPS 2025spotlightarXiv:2502.10138

Regret Bounds for Adversarial Contextual Bandits with General Function Approximation and Delayed Feedback

Orin Levy, Liad Erez, Alon Peled-Cohen et al.

NEURIPS 2025spotlightarXiv:2510.09127

Regretful Decisions under Label Noise

Sujay Nagaraj, Yang Liu, Flavio Calmon et al.

ICLR 2025posterarXiv:2504.09330
3
citations

REINFORCEMENT LEARNING FOR INDIVIDUAL OPTIMAL POLICY FROM HETEROGENEOUS DATA

Rui Miao, Babak Shahbaba, Annie Qu

NEURIPS 2025posterarXiv:2505.09496
1
citations

Robust Contextual Pricing

Anupam Gupta, Guru Guruganesh, Renato Leme et al.

NEURIPS 2025poster

Stable Matching with Ties: Approximation Ratios and Learning

Shiyun Lin, Simon Mauras, Nadav Merlis et al.

NEURIPS 2025posterarXiv:2411.03270
2
citations

Tightening Regret Lower and Upper Bounds in Restless Rising Bandits

Cristiano Migali, Marco Mussi, Gianmarco Genalti et al.

NEURIPS 2025poster