Poster "regret minimization" Papers
43 papers found
Conference
Adapting to Stochastic and Adversarial Losses in Episodic MDPs with Aggregate Bandit Feedback
Shinji Ito, Kevin Jamieson, Haipeng Luo et al.
Almost Optimal Batch-Regret Tradeoff for Batch Linear Contextual Bandits
Zihan Zhang, Xiangyang Ji, Yuan Zhou
An Improved Algorithm for Adversarial Linear Contextual Bandits via Reduction
Tim van Erven, Jack Mayo, Julia Olkhovskaya et al.
An Online Learning Theory of Trading-Volume Maximization
Tommaso Cesari, Roberto Colomboni
Causal LLM Routing: End-to-End Regret Minimization from Observational Data
Asterios Tsiourvas, Wei Sun, Georgia Perakis
Comparing Uniform Price and Discriminatory Multi-Unit Auctions through Regret Minimization
Marius Potfer, Vianney Perchet
Contextual Dynamic Pricing with Heterogeneous Buyers
Thodoris Lykouris, Sloan Nietert, Princewill Okoroafor et al.
Feature-Based Online Bilateral Trade
Solenne Gaucher, Martino Bernasconi, Matteo Castiglioni et al.
Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment
Aadirupa Saha, Pierre Gaillard
Improved Regret and Contextual Linear Extension for Pandora's Box and Prophet Inequality
Junyan Liu, Ziyun Chen, Kun Wang et al.
Learning from Imperfect Human Feedback: A Tale from Corruption-Robust Dueling
Yuwei Cheng, Fan Yao, Xuefeng Liu et al.
Learning to price with resource constraints: from full information to machine-learned prices
Ruicheng Ao, Jiashuo Jiang, David Simchi-Levi
Linear Bandits with Memory
Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi
Markov Persuasion Processes: Learning to Persuade From Scratch
Francesco Bacchiocchi, Francesco Emanuele Stradi, Matteo Castiglioni et al.
Near-Optimal Regret-Queue Length Tradeoff in Online Learning for Two-Sided Markets
Zixian Yang, Sushil Varma, Lei Ying
No-Regret Online Autobidding Algorithms in First-price Auctions
Yilin LI, Yuan Deng, Wei Tang et al.
Online Learning in the Repeated Mediated Newsvendor Problem
Nataša Bolić, Tom Cesari, Roberto Colomboni et al.
Optimal Regret of Bandits under Differential Privacy
Achraf Azize, Yulian Wu, Junya Honda et al.
Regretful Decisions under Label Noise
Sujay Nagaraj, Yang Liu, Flavio Calmon et al.
REINFORCEMENT LEARNING FOR INDIVIDUAL OPTIMAL POLICY FROM HETEROGENEOUS DATA
Rui Miao, Babak Shahbaba, Annie Qu
Robust Contextual Pricing
Anupam Gupta, Guru Guruganesh, Renato Leme et al.
Stable Matching with Ties: Approximation Ratios and Learning
Shiyun Lin, Simon Mauras, Nadav Merlis et al.
Tightening Regret Lower and Upper Bounds in Restless Rising Bandits
Cristiano Migali, Marco Mussi, Gianmarco Genalti et al.
Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization
Neelkamal Bhuyan, Debankur Mukherjee, Adam Wierman
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.
Eluder-based Regret for Stochastic Contextual MDPs
Orin Levy, Asaf Cassel, Alon Cohen et al.
Equilibrium of Data Markets with Externality
Safwan Hossain, Yiling Chen
Graph-Triggered Rising Bandits
Gianmarco Genalti, Marco Mussi, Nicola Gatti et al.
Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements
Naman Agarwal, Satyen Kale, Karan Singh et al.
Incentivized Learning in Principal-Agent Bandit Games
Antoine Scheid, Daniil Tiapkin, Etienne Boursier et al.
Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery
Yassir Jedra, William Réveillard, Stefan Stojanovic et al.
Monotone Individual Fairness
Yahav Bechavod
Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning
Joon Suk Huh, Kirthevasan Kandasamy
Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
Asaf Cassel, Haipeng Luo, Aviv Rosenberg et al.
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints
Dan Qiao, Yu-Xiang Wang
No-Regret Reinforcement Learning in Smooth MDPs
Davide Maran, Alberto Maria Metelli, Matteo Papini et al.
Online Learning in CMDPs: Handling Stochastic and Adversarial Constraints
Francesco Emanuele Stradi, Jacopo Germano, Gianmarco Genalti et al.
Online Learning with Bounded Recall
Jon Schneider, Kiran Vodrahalli
Online Matrix Completion: A Collaborative Approach with Hott Items
Dheeraj Baby, Soumyabrata Pal
Projection-Free Online Convex Optimization with Time-Varying Constraints
Dan Garber, Ben Kretzu
Quantum Algorithm for Online Exp-concave Optimization
Jianhao He, Chengchang Liu, Xutong Liu et al.
Rate-Optimal Policy Optimization for Linear Markov Decision Processes
Uri Sherman, Alon Cohen, Tomer Koren et al.
Test-Time Regret Minimization in Meta Reinforcement Learning
Mirco Mutti, Aviv Tamar