arXiv Machine Learning
Jul 2

Distributed Online Bandit Submodular Maximization with Bounded Sampling Violations

arXiv:2607. 00680v1 Announce Type: new Abstract: We study distributed online submodular maximization under partition matroid constraints, in which multiple agents select a limited number of actions from their own subsets sequentially to maximize the cumulative value of a sequence of objective functions.

By Bin Du, Chang Liu, Dingqi Zhu, Lintao Ye, Dengfeng Sun