4 papers
Multi-Agent Combinatorial-Multi-Armed-Bandit framework for the Submodular Welfare Problem under Bandit Feedback
Subham Pokhriyal, Shweta Jain, Vaneet Aggarwal
We study the \emph{Submodular Welfare Problem} (SWP), where items are partitioned among agents with monotone submodular utilities to maximize the total welfare under \emph{bandit f…
A Resilience Framework for Bi-Criteria Combinatorial Optimization with Bandit Feedback
Vaneet Aggarwal, Shweta Jain, Subham Pokhriyal +1
We study bi-criteria combinatorial optimization under noisy function evaluations. While resilience and black-box offline-to-online reductions have been studied in single-objective…
Simultaneously Achieving Group Exposure Fairness and Within-Group Meritocracy in Stochastic Bandits
Subham Pokhriyal, Shweta Jain, Ganesh Ghalme +2
Existing approaches to fairness in stochastic multi-armed bandits (MAB) primarily focus on exposure guarantee to individual arms. When arms are naturally grouped by certain attribu…
Learning from Satisfying Assignments Using Risk Minimization
Manjish Pal. Subham Pokhriyal
In this paper we consider the problem of Learning from Satisfying Assignments introduced by \cite{1} of finding a distribution that is a close approximation to the uniform distribu…