Abolfazl Hashemi
Abolfazl Hashemi
Assistant Professor of ECE, Purdue University
Zweryfikowany adres z purdue.edu - Strona główna
Cytowane przez
Cytowane przez
Faster non-convex federated learning via global and local momentum
R Das, A Acharya, A Hashemi, S Sanghavi, IS Dhillon, U Topcu
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Randomized greedy sensor selection: Leveraging weak submodularity
A Hashemi, M Ghasemi, H Vikalo, U Topcu
IEEE Transactions on Automatic Control, Jan 2021, 2021
Generalization bounds for sparse random feature expansions
A Hashemi, H Schaeffer, R Shi, U Topcu, G Tran, R Ward
Applied and Computational Harmonic Analysis, 2023
A randomized greedy algorithm for near-optimal sensor scheduling in large-scale sensor networks
A Hashemi, M Ghasemi, H Vikalo, U Topcu
2018 Annual American Control Conference (ACC), 1027-1032, 2018
On the benefits of multiple gossip steps in communication-constrained decentralized Federated Learning
A Hashemi, A Acharya, R Das, H Vikalo, S Sanghavi, I Dhillon
IEEE Transactions on Parallel and Distributed Systems, 2021
Sparse tensor decomposition for haplotype assembly of diploids and polyploids
A Hashemi, B Zhu, H Vikalo
BMC genomics 19, 1-15, 2018
Sparse linear regression via generalized orthogonal least-squares
A Hashemi, H Vikalo
2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2016
Online topology inference from streaming stationary graph signals
R Shafipour, A Hashemi, G Mateos, H Vikalo
2019 IEEE Data Science Workshop (DSW), 140-144, 2019
Submodular observation selection and information gathering for quadratic models
A Hashemi, M Ghasemi, H Vikalo, U Topcu
2019 International Conference on Machine Learning (ICML) 1 (1), 1-10, 2019
Robust Training in High Dimensions via Block Coordinate Geometric Median Descent
A Acharya, A Hashemi, P Jain, S Sanghavi, IS Dhillon, U Topcu
The 25th International Conference on Artificial Intelligence and Statistics …, 2022
Accelerated orthogonal least-squares for large-scale sparse reconstruction
A Hashemi, H Vikalo
Digital Signal Processing 82, 91-105, 2018
On the convergence of decentralized federated learning under imperfect information sharing
VP Chellapandi, A Upadhyay, A Hashemi, SH Żak
IEEE Control Systems Letters, 2023
Evolutionary self-expressive models for subspace clustering
A Hashemi, H Vikalo
IEEE Journal of Selected Topics in Signal Processing 12 (6), 1534-1546, 2018
Communication-efficient algorithms for decentralized optimization over directed graphs
Y Chen, A Hashemi, H Vikalo
arXiv e-prints, arXiv: 2005.13189, 2020
Communication-Efficient Variance-Reduced Decentralized Stochastic Optimization over Time-Varying Directed Graphs
Y Chen, A Hashemi, H Vikalo
IEEE Transactions on Automatic Control, 2021
No-regret learning in dynamic Stackelberg games
N Lauffer, M Ghasemi, A Hashemi, Y Savas, U Topcu
IEEE Transactions on Automatic Control, 2023
Differentially private federated learning with normalized updates
R Das, A Hashemi, IS Dhillon
OPT 2022: Optimization for Machine Learning (NeurIPS 2022 Workshop), 2022
On the Benefits of Progressively Increasing Sampling Sizes in Stochastic Greedy Weak Submodular Maximization
A Hashemi, H Vikalo, G de Veciana
IEEE Transactions on Signal Processing, 2022
Sampling and reconstruction of graph signals via weak submodularity and semidefinite relaxation
A Hashemi, R Shafipour, H Vikalo, G Mateos
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
Evolutionary subspace clustering: discovering structure in self-expressive time-series data
A Hashemi, H Vikalo
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
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