2024 "regret minimization" Papers

24 papers found

Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization

Neelkamal Bhuyan, Debankur Mukherjee, Adam Wierman

ICML 2024posterarXiv:2311.00181

Communication-Efficient Collaborative Regret Minimization in Multi-Armed Bandits

Nikolai Karpov, Qin Zhang

AAAI 2024paperarXiv:2301.11442
2
citations

Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods

Wenzhi Gao, Chunlin Sun, Chenyu Xue et al.

ICML 2024posterarXiv:2402.07108

Eluder-based Regret for Stochastic Contextual MDPs

Orin Levy, Asaf Cassel, Alon Cohen et al.

ICML 2024posterarXiv:2211.14932

Equilibrium of Data Markets with Externality

Safwan Hossain, Yiling Chen

ICML 2024posterarXiv:2302.08012

Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs

Tianyuan Jin, Hao-Lun Hsu, William Chang et al.

AAAI 2024paperarXiv:2312.15549
2
citations

Graph-Triggered Rising Bandits

Gianmarco Genalti, Marco Mussi, Nicola Gatti et al.

ICML 2024poster

Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements

Naman Agarwal, Satyen Kale, Karan Singh et al.

ICML 2024poster

Incentivized Learning in Principal-Agent Bandit Games

Antoine Scheid, Daniil Tiapkin, Etienne Boursier et al.

ICML 2024posterarXiv:2403.03811

Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery

Yassir Jedra, William Réveillard, Stefan Stojanovic et al.

ICML 2024posterarXiv:2402.15739

Monotone Individual Fairness

Yahav Bechavod

ICML 2024posterarXiv:2403.06812

Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning

Joon Suk Huh, Kirthevasan Kandasamy

ICML 2024posterarXiv:2407.04898

Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback

Asaf Cassel, Haipeng Luo, Aviv Rosenberg et al.

ICML 2024posterarXiv:2405.07637

Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints

Dan Qiao, Yu-Xiang Wang

ICML 2024posterarXiv:2402.01111

No-Regret Reinforcement Learning in Smooth MDPs

Davide Maran, Alberto Maria Metelli, Matteo Papini et al.

ICML 2024posterarXiv:2402.03792

Online Learning in CMDPs: Handling Stochastic and Adversarial Constraints

Francesco Emanuele Stradi, Jacopo Germano, Gianmarco Genalti et al.

ICML 2024poster

Online Learning with Bounded Recall

Jon Schneider, Kiran Vodrahalli

ICML 2024posterarXiv:2205.14519

Online Matrix Completion: A Collaborative Approach with Hott Items

Dheeraj Baby, Soumyabrata Pal

ICML 2024posterarXiv:2408.05843

Pricing with Contextual Elasticity and Heteroscedastic Valuation

Jianyu Xu, Yu-Xiang Wang

ICML 2024spotlightarXiv:2312.15999

Projection-Free Online Convex Optimization with Time-Varying Constraints

Dan Garber, Ben Kretzu

ICML 2024posterarXiv:2402.08799

Prospective Side Information for Latent MDPs

Jeongyeol Kwon, Yonathan Efroni, Shie Mannor et al.

ICML 2024spotlightarXiv:2310.07596

Quantum Algorithm for Online Exp-concave Optimization

Jianhao He, Chengchang Liu, Xutong Liu et al.

ICML 2024posterarXiv:2410.19688

Rate-Optimal Policy Optimization for Linear Markov Decision Processes

Uri Sherman, Alon Cohen, Tomer Koren et al.

ICML 2024posterarXiv:2308.14642

Test-Time Regret Minimization in Meta Reinforcement Learning

Mirco Mutti, Aviv Tamar

ICML 2024posterarXiv:2406.02282