No-Regret is not enough! Bandits with General Constraints through Adaptive Regret Minimization

10 May 2024

Papers citing "No-Regret is not enough! Bandits with General Constraints through Adaptive Regret Minimization"

7 / 7 papers shown

Title
Online Two-Sided Markets: Many Buyers Enhance Learning Anna Lunghi Matteo Castiglioni A. Marchesi 57 0 0 03 Mar 2025
Bandits with Anytime Knapsacks Eray Can Elumar Cem Tekin Osman Yagan 107 0 0 30 Jan 2025
Learning to Explore with Lagrangians for Bandits under Unknown Linear Constraints Udvas Das Debabrota Basu 29 0 0 24 Oct 2024
Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints Martino Bernasconi Matteo Castiglioni A. Celli Federico Fusco 31 2 0 25 May 2024
Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression Aleksandrs Slivkins Xingyu Zhou Karthik Abinav Sankararaman Dylan J. Foster 61 22 0 14 Nov 2022
Online Resource Allocation under Horizon Uncertainty S. Balseiro Christian Kroer Rachitesh Kumar 23 15 0 27 Jun 2022
Resourceful Contextual Bandits Ashwinkumar Badanidiyuru John Langford Aleksandrs Slivkins 40 117 0 27 Feb 2014