61 citations · 179 across the 39 of their papers we have counts for
5 papers · 1 filter
Anonymous Bandits for Multi-User Systems
Hossein Esfandiari, Vahab Mirrokni, Jon Schneider
In this work, we present and study a new framework for online learning in systems with multiple users that provide user anonymity. Specifically, we extend the notion of bandits to…
Replicable Bandits
Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi +3
In this paper, we introduce the notion of replicable policies in the context of stochastic bandits, one of the canonical problems in interactive learning. A policy in the bandit en…
Smooth Anonymity for Sparse Graphs
Alessandro Epasto, Hossein Esfandiari, Vahab Mirrokni +1
When working with user data providing well-defined privacy guarantees is paramount. In this work, we aim to manipulate and share an entire sparse dataset with a third party private…
Tackling Provably Hard Representative Selection via Graph Neural Networks
Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari +4
Representative Selection (RS) is the problem of finding a small subset of exemplars from a dataset that is representative of the dataset. In this paper, we study RS for attributed…
Improved Approximations for Euclidean -means and -median, via Nested Quasi-Independent Sets
Vincent Cohen-Addad, Hossein Esfandiari, Vahab Mirrokni +1
Motivated by data analysis and machine learning applications, we consider the popular high-dimensional Euclidean -median and -means problems. We propose a new primal-dual alg…