7 citations · 21 across the 7 of their papers we have counts for
13 papers
No-Regret Learning in Dynamic Stackelberg Games
Niklas Lauffer, Mahsa Ghasemi, Abolfazl Hashemi +2
In a Stackelberg game, a leader commits to a randomized strategy, and a follower chooses their best strategy in response. We consider an extension of a standard Stackelberg game, c…
Robust Training in High Dimensions via Block Coordinate Geometric Median Descent
Anish Acharya, Abolfazl Hashemi, Prateek Jain +3
Geometric median (\textsc{Gm}) is a classical method in statistics for achieving a robust estimation of the uncorrupted data; under gross corruption, it achieves the optimal breakd…
Physical-Layer Security via Distributed Beamforming in the Presence of Adversaries with Unknown Locations
Yagiz Savas, Abolfazl Hashemi, Abraham P. Vinod +2
We study the problem of securely communicating a sequence of information bits with a client in the presence of multiple adversaries at unknown locations in the environment. We assu…
Faster Non-Convex Federated Learning via Global and Local Momentum
Rudrajit Das, Anish Acharya, Abolfazl Hashemi +3
We propose \texttt{FedGLOMO}, a novel federated learning (FL) algorithm with an iteration complexity of to converge to an -stationary point (i.e., $\math…
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization
Abolfazl Hashemi, Anish Acharya, Rudrajit Das +3
In decentralized optimization, it is common algorithmic practice to have nodes interleave (local) gradient descent iterations with gossip (i.e. averaging over the network) steps. M…
Identifying Sparse Low-Dimensional Structures in Markov Chains: A Nonnegative Matrix Factorization Approach
Mahsa Ghasemi, Abolfazl Hashemi, Haris Vikalo +1
We consider the problem of learning low-dimensional representations for large-scale Markov chains. We formulate the task of representation learning as that of mapping the state spa…