20 citations · 36 across the 13 of their papers we have counts for
14 papers
Stay or Stray - A Dynamical Systems Viewpoint of Popularity Bias
Sarvesh Shashidhar, Lankireddy Prabhat, Arpit Agarwal +3
Popularity bias in recommendation systems arises when a majority user class generates disproportionate interaction data, causing the system to increasingly favour it while degradin…
Finding the Signal in the Spam: Jointly Learning Rewards and Worker Reliability from Pairwise Comparisons
Kaustubh Shivshankar Shejole, Tanish Agarwal, Arpit Agarwal +1
The problem of learning from pairwise comparisons has been widely studied across many domains such as recommendation systems, social choice, and more recently, fine-tuning large la…
When Can We Track Significant Preference Shifts in Dueling Bandits?
Joe Suk, Arpit Agarwal
The -armed dueling bandits problem, where the feedback is in the form of noisy pairwise preferences, has been widely studied due its applications in information retrieval, recom…
Online Recommendations for Agents with Discounted Adaptive Preferences
Arpit Agarwal, William Brown
We consider a bandit recommendations problem in which an agent's preferences (representing selection probabilities over recommended items) evolve as a function of past selections,…
Diversified Recommendations for Agents with Adaptive Preferences
Arpit Agarwal, William Brown
When an Agent visits a platform recommending a menu of content to select from, their choice of item depends not only on fixed preferences, but also on their prior engagements with…
An Asymptotically Optimal Batched Algorithm for the Dueling Bandit Problem
Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan
We study the -armed dueling bandit problem, a variation of the traditional multi-armed bandit problem in which feedback is obtained in the form of pairwise comparisons. Previous…