Faster non-convex federated learning via global and local momentum R Das, A Acharya, A Hashemi, S Sanghavi, IS Dhillon, U Topcu Uncertainty in Artificial Intelligence, 496-506, 2022 | 76 | 2022 |
Randomized greedy sensor selection: Leveraging weak submodularity A Hashemi, M Ghasemi, H Vikalo, U Topcu IEEE Transactions on Automatic Control, Jan 2021, 2021 | 62 | 2021 |
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 | 39 | 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 33 (11), 2727-2739, 2021 | 34 | 2021 |
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 | 32 | 2022 |
Generalization bounds for sparse random feature expansions A Hashemi, H Schaeffer, R Shi, U Topcu, G Tran, R Ward Applied and Computational Harmonic Analysis 62, 310-330, 2023 | 29 | 2023 |
Sparse tensor decomposition for haplotype assembly of diploids and polyploids A Hashemi, B Zhu, H Vikalo BMC genomics 19, 1-15, 2018 | 27 | 2018 |
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 | 25 | 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 | 25 | 2019 |
Sparse linear regression via generalized orthogonal least-squares A Hashemi, H Vikalo 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2016 | 25 | 2016 |
On the convergence of decentralized federated learning under imperfect information sharing VP Chellapandi, A Upadhyay, A Hashemi, SH Żak IEEE Control Systems Letters, 2023 | 22 | 2023 |
Accelerated orthogonal least-squares for large-scale sparse reconstruction A Hashemi, H Vikalo Digital Signal Processing 82, 91-105, 2018 | 18 | 2018 |
No-regret learning in dynamic stackelberg games N Lauffer, M Ghasemi, A Hashemi, Y Savas, U Topcu IEEE Transactions on Automatic Control, 2023 | 16 | 2023 |
Generalization bounds for sparse random feature expansions A Hashemi, H Schaeffer, R Shi, U Topcu, G Tran, R Ward arXiv preprint arXiv:2103.03191, 2021 | 15 | 2021 |
Decentralized optimization on time-varying directed graphs under communication constraints Y Chen, A Hashemi, H Vikalo ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 14 | 2021 |
Evolutionary self-expressive models for subspace clustering A Hashemi, H Vikalo IEEE Journal of Selected Topics in Signal Processing 12 (6), 1534-1546, 2018 | 14 | 2018 |
Asynchronous federated reinforcement learning with policy gradient updates: Algorithm design and convergence analysis G Lan, DJ Han, A Hashemi, V Aggarwal, CG Brinton arXiv preprint arXiv:2404.08003, 2024 | 13 | 2024 |
Communication-Efficient Variance-Reduced Decentralized Stochastic Optimization over Time-Varying Directed Graphs Y Chen, A Hashemi, H Vikalo IEEE Transactions on Automatic Control, 2021 | 13 | 2021 |
Improved convergence rates for non-convex federated learning with compression R Das, A Hashemi, S Sanghavi, IS Dhillon arXiv preprint arXiv:2012.04061, 2020 | 10 | 2020 |
Towards Accelerated Greedy Sampling and Reconstruction of Bandlimited Graph Signals A Hashemi, R Shafipour, H Vikalo, G Mateos Elsevier Signal Processing, 2022 | 8* | 2022 |