1 citations · 1 across the 4 of their papers we have counts for
4 papers
Learning to Price with Persuasion
Maria-Florina Balcan, Tejas Pagare, Karan Singh
Motivated by modern marketplaces, where the platform or the seller routinely gathers detailed user profiles, we study a novel learning theoretic model that simultaneously involves…
Optimal Algorithms for Bandit Learning in Matching Markets
Tejas Pagare, Agniv Bandyopadhyay, Sandeep Juneja
We study the problem of pure exploration in matching markets under uncertain preferences, where the goal is to identify a stable matching with confidence parameter and minimal…
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…
Full Gradient Deep Reinforcement Learning for Average-Reward Criterion
Tejas Pagare, Vivek Borkar, Konstantin Avrachenkov
We extend the provably convergent Full Gradient DQN algorithm for discounted reward Markov decision processes from Avrachenkov et al. (2021) to average reward problems. We experime…