3 citations · 8 across the 11 of their papers we have counts for
7 papers · 1 filter
Does Feedback Help in Bandits with Arm Erasures?
Merve Karakas, Osama Hanna, Lin F. Yang +1
We study a distributed multi-armed bandit (MAB) problem over arm erasure channels, motivated by the increasing adoption of MAB algorithms over communication-constrained networks. I…
Multi-Agent Bandit Learning through Heterogeneous Action Erasure Channels
Osama A. Hanna, Merve Karakas, Lin F. Yang +1
Multi-Armed Bandit (MAB) systems are witnessing an upswing in applications within multi-agent distributed environments, leading to the advancement of collaborative MAB algorithms.…
Differentially Private Stochastic Linear Bandits: (Almost) for Free
Osama A. Hanna, Antonious M. Girgis, Christina Fragouli +1
In this paper, we propose differentially private algorithms for the problem of stochastic linear bandits in the central, local and shuffled models. In the central model, we achieve…
Learning in Distributed Contextual Linear Bandits Without Sharing the Context
Osama A. Hanna, Lin F. Yang, Christina Fragouli
Contextual linear bandits is a rich and theoretically important model that has many practical applications. Recently, this setup gained a lot of interest in applications over wirel…
Solving Multi-Arm Bandit Using a Few Bits of Communication
Osama A. Hanna, Lin F. Yang, Christina Fragouli
The multi-armed bandit (MAB) problem is an active learning framework that aims to select the best among a set of actions by sequentially observing rewards. Recently, it has become…
Quantizing data for distributed learning
Osama A. Hanna, Yahya H. Ezzeldin, Christina Fragouli +1
We consider machine learning applications that train a model by leveraging data distributed over a trusted network, where communication constraints can create a performance bottlen…
On Distributed Quantization for Classification
Osama A. Hanna, Yahya H. Ezzeldin, Tara Sadjadpour +2
We consider the problem of distributed feature quantization, where the goal is to enable a pretrained classifier at a central node to carry out its classification on features that…