4 papers
Near Optimal Best Arm Identification for Clustered Bandits
Yash, Nikhil Karamchandani, Avishek Ghosh
This work investigates the problem of best arm identification for multi-agent multi-armed bandits. We consider agents grouped into clusters, where each cluster solves a sto…
Incentivize Contribution and Learn Parameters Too: Federated Learning with Strategic Data Owners
Drashthi Doshi, Aditya Vema Reddy Kesari, Avishek Ghosh +2
Classical federated learning (FL) assumes that the clients have a limited amount of noisy data with which they voluntarily participate and contribute towards learning a global, mor…
Competing Bandits in Decentralized Contextual Matching Markets
Satush Parikh, Soumya Basu, Avishek Ghosh +1
Sequential learning in a multi-agent resource constrained matching market has received significant interest in the past few years. We study decentralized learning in two-sided matc…
Explore-then-Commit Algorithms for Decentralized Two-Sided Matching Markets
Tejas Pagare, Avishek Ghosh
Online learning in a decentralized two-sided matching markets, where the demand-side (players) compete to match with the supply-side (arms), has received substantial interest becau…