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Mher Safaryan
Mher Safaryan
Postdoctoral MSCA Fellow, IST Austria
Verified email at ist.ac.at - Homepage
Title
Cited by
Cited by
Year
On Biased Compression for Distributed Learning
A Beznosikov, S Horváth, P Richtárik, M Safaryan
Journal of Machine Learning Research (JMLR), 2023, 2020
1422020
FedNL: Making Newton-type methods applicable to federated learning
M Safaryan, R Islamov, X Qian, P Richtárik
International Conference on Machine Learning (ICML), 2022, 2021
642021
Optimal gradient compression for distributed and federated learning
A Albasyoni, M Safaryan, L Condat, P Richtárik
arXiv preprint arXiv:2010.03246, 2020
502020
Uncertainty principle for communication compression in distributed and federated learning and the search for an optimal compressor
M Safaryan, E Shulgin, P Richtárik
Information and Inference: A Journal of the IMA, 2021, 2020
472020
Stochastic Sign Descent Methods: New Algorithms and Better Theory
M Safaryan, P Richtárik
International Conference on Machine Learning (ICML), 2021, 2019
43*2019
Smoothness matrices beat smoothness constants: Better communication compression techniques for distributed optimization
M Safaryan, F Hanzely, P Richtárik
Advances in Neural Information Processing Systems (NeurIPS) 34, 25688-25702, 2021
202021
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning
X Qian, R Islamov, M Safaryan, P Richtárik
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021
172021
Construction of free g-dimonoids
Y Movsisyan, S Davidov, M Safaryan
Algebra and discrete mathematics, 2014
172014
Theoretically Better and Numerically Faster Distributed Optimization with Smoothness-Aware Quantization Techniques
B Wang, M Safaryan, P Richtárik
Advances in Neural Information Processing Systems (NeurIPS) 2022, 2021
10*2021
Gradskip: Communication-accelerated local gradient methods with better computational complexity
A Maranjyan, M Safaryan, P Richtárik
arXiv preprint arXiv:2210.16402, 2022
92022
On generalizations of Fatou’s theorem for the integrals with general kernels
GA Karagulyan, MH Safaryan
The Journal of Geometric Analysis 25, 1459-1475, 2015
92015
Distributed Newton-type methods with communication compression and bernoulli aggregation
R Islamov, X Qian, S Hanzely, M Safaryan, P Richtárik
Transactions on Machine Learning Research (TMLR), 2023, 2022
72022
On a theorem of Littlewood
GA Karagulyan, MH Safaryan
Hokkaido Mathematical Journal 46 (1), 87-106, 2017
62017
On an equivalence for differentiation bases of dyadic rectangles
GA Karagulyan, DA Karagulyan, MH Safaryan
Colloquium Mathematicum 146 (2), 295-307, 2017
62017
On Generalizations of Fatou’s Theorem in for Convolution Integrals with General Kernels
MH Safaryan
The Journal of Geometric Analysis 31 (4), 3280-3299, 2021
42021
On an equivalency of rare differentiation bases of rectangles
MH Safaryan
Journal of Contemporary Mathematical Analysis (Armenian Academy of Sciences …, 2018
42018
AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms
R Islamov, M Safaryan, D Alistarh
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2023
22023
Knowledge Distillation Performs Partial Variance Reduction
M Safaryan, A Peste, D Alistarh
Advances in Neural Information Processing Systems (NeurIPS) 2023, 2023
2023
On estimates for maximal operators associated with tangential regions
M Safaryan
arXiv preprint arXiv:2202.08693, 2022
2022
A surprisingly effective algorithm for the simplification of integrals and sums arising in the partial differential equations and numerical methods
DA Gomes, M Safaryan, RL Ribeiro, M Sayyari
2020
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