4 citations · 11 across the 4 of their papers we have counts for
4 papers
Communication-Efficient Zeroth-Order Distributed Online Optimization: Algorithm, Theory, and Applications
Ege C. Kaya, M. Berk Sahin, Abolfazl Hashemi
This paper focuses on a multi-agent zeroth-order online optimization problem in a federated learning setting for target tracking. The agents only sense their current distances to t…
Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data
Sai Aparna Aketi, Abolfazl Hashemi, Kaushik Roy
Decentralized learning enables the training of deep learning models over large distributed datasets generated at different locations, without the need for a central server. However…
On the Convergence of Decentralized Federated Learning Under Imperfect Information Sharing
Vishnu Pandi Chellapandi, Antesh Upadhyay, Abolfazl Hashemi +1
Decentralized learning and optimization is a central problem in control that encompasses several existing and emerging applications, such as federated learning. While there exists…
Sparse recovery via Orthogonal Least-Squares under presence of Noise
Abolfazl Hashemi, Haris Vikalo
We consider the Orthogonal Least-Squares (OLS) algorithm for the recovery of a -dimensional -sparse signal from a low number of noisy linear measurements. The Exact Recovery…