Abolfazl Hashemi | DeepAI

AI Chat

Featured Co-authors

Ufuk Topcu
123 publications
Kaushik Roy
121 publications
Prateek Jain
87 publications
Sujay Sanghavi
58 publications
Scott Niekum
45 publications
Inderjit S. Dhillon
43 publications
Rachel Ward
42 publications
Haris Vikalo
26 publications
Gonzalo Mateos
22 publications
Inderjit Dhillon
18 publications
Hayden Schaeffer
14 publications

∙ 07/14/2023

Improved Convergence Analysis and SNR Control Strategies for Federated Learning in the Presence of Noise

We propose an improved convergence analysis technique that characterizes...

0 Antesh Upadhyay, et al. ∙

∙ 06/09/2023

Communication-Efficient Zeroth-Order Distributed Online Optimization: Algorithm, Theory, and Applications

This paper focuses on a multi-agent zeroth-order online optimization pro...

0 Ege C. Kaya, et al. ∙

∙ 05/08/2023

Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data

Decentralized learning enables the training of deep learning models over...

0 Sai Aparna Aketi, et al. ∙

∙ 03/19/2023

On the Convergence of Decentralized Federated Learning Under Imperfect Information Sharing

Decentralized learning and optimization is a central problem in control ...

0 Vishnu Pandi Chellapandi, et al. ∙

∙ 02/10/2022

No-Regret Learning in Dynamic Stackelberg Games

In a Stackelberg game, a leader commits to a randomized strategy, and a ...

0 Niklas Lauffer, et al. ∙

∙ 06/30/2021

Robust Generative Adversarial Imitation Learning via Local Lipschitzness

We explore methodologies to improve the robustness of generative adversa...

0 Farzan Memarian, et al. ∙

∙ 06/16/2021

Robust Training in High Dimensions via Block Coordinate Geometric Median Descent

Geometric median (Gm) is a classical method in statistics for achieving ...

12 Anish Acharya, et al. ∙

∙ 06/13/2021

DP-NormFedAvg: Normalizing Client Updates for Privacy-Preserving Federated Learning

In this paper, we focus on facilitating differentially private quantized...

20 Rudrajit Das, et al. ∙

∙ 03/04/2021

Function Approximation via Sparse Random Features

Random feature methods have been successful in various machine learning ...

40 Abolfazl Hashemi, et al. ∙

∙ 12/07/2020

Improved Convergence Rates for Non-Convex Federated Learning with Compression

Federated learning is a new distributed learning paradigm that enables e...

14 Rudrajit Das, et al. ∙

∙ 11/20/2020

On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization

In decentralized optimization, it is common algorithmic practice to have...

2 Abolfazl Hashemi, et al. ∙

∙ 09/27/2019

Identifying Low-Dimensional Structures in Markov Chains: A Nonnegative Matrix Factorization Approach

A variety of queries about stochastic systems boil down to study of Mark...

0 Mahsa Ghasemi, et al. ∙

∙ 07/22/2019

Stochastic-Greedy++: Closing the Optimality Gap in Exact Weak Submodular Maximization

Many problems in discrete optimization can be formulated as the task of ...

0 Gustavo de Veciana, et al. ∙

∙ 10/29/2018

Evolutionary Self-Expressive Models for Subspace Clustering

The problem of organizing data that evolves over time into clusters is e...

0 Abolfazl Hashemi, et al. ∙

∙ 10/31/2017

Sampling and Reconstruction of Graph Signals via Weak Submodularity and Semidefinite Relaxation

We study the problem of sampling a bandlimited graph signal in the prese...

0 Abolfazl Hashemi, et al. ∙

∙ 10/31/2017

Accelerated Sparse Subspace Clustering

State-of-the-art algorithms for sparse subspace clustering perform spect...

0 Abolfazl Hashemi, et al. ∙

∙ 08/08/2016

Sparse recovery via Orthogonal Least-Squares under presence of Noise

We consider the Orthogonal Least-Squares (OLS) algorithm for the recover...

0 Abolfazl Hashemi, et al. ∙

∙ 08/08/2016

Sampling Requirements and Accelerated Schemes for Sparse Linear Regression with Orthogonal Least-Squares

The Orthogonal Least Squares (OLS) algorithm sequentially selects column...

0 Abolfazl Hashemi, et al. ∙

∙ 02/22/2016

Sparse Linear Regression via Generalized Orthogonal Least-Squares

Sparse linear regression, which entails finding a sparse solution to an ...

0 Abolfazl Hashemi, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world