Contextual Bandits with Packing and Covering Constraints: A Modular
Lagrangian Approach via Regression

Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression

14 November 2022

Aleksandrs Slivkins

Karthik Abinav Sankararaman

Dylan J. Foster

Papers citing "Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression"

6 / 6 papers shown

Title
A New Benchmark for Online Learning with Budget-Balancing Constraints M. Braverman Jingyi Liu Jieming Mao Jon Schneider Eric Xue 50 0 0 19 Mar 2025
Bandits with Anytime Knapsacks Eray Can Elumar Cem Tekin Osman Yagan 103 0 0 30 Jan 2025
Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints Martino Bernasconi Matteo Castiglioni A. Celli Federico Fusco 29 2 0 25 May 2024
No-Regret Algorithms in non-Truthful Auctions with Budget and ROI Constraints Gagan Aggarwal Giannis Fikioris Mingfei Zhao 32 5 0 15 Apr 2024
Kernel-based methods for bandit convex optimization Sébastien Bubeck Ronen Eldan Y. Lee 76 163 0 11 Jul 2016
Resourceful Contextual Bandits Ashwinkumar Badanidiyuru John Langford Aleksandrs Slivkins 38 117 0 27 Feb 2014