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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
1972020
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
922021
Optimal Gradient Compression for Distributed and Federated Learning
A Albasyoni, M Safaryan, L Condat, P Richtárik
arXiv preprint arXiv:2010.03246, 2020
652020
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
642020
Stochastic Sign Descent Methods: New Algorithms and Better Theory
M Safaryan, P Richtárik
International Conference on Machine Learning (ICML), 2021, 2019
55*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
322021
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
242021
Construction of free g-dimonoids
Y Movsisyan, S Davidov, M Safaryan
Algebra and discrete mathematics, 2014
182014
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
15*2021
AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms
R Islamov, M Safaryan, D Alistarh
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2023
122023
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
122022
Gradskip: Communication-accelerated local gradient methods with better computational complexity
A Maranjyan, M Safaryan, P Richtárik
arXiv preprint arXiv:2210.16402, 2022
112022
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
102015
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
82021
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
Colloq. Math 146 (2), 295-307, 2017
62017
Microadam: Accurate adaptive optimization with low space overhead and provable convergence, 2024
IV Modoranu, M Safaryan, G Malinovsky, E Kurtic, T Robert, P Richtarik, ...
URL https://arxiv. org/abs/2405.15593, 0
6
On an equivalency of rare differentiation bases of rectangles
MH Safaryan
Journal of Contemporary Mathematical Analysis (Armenian Academy of Sciences …, 2018
52018
Knowledge Distillation Performs Partial Variance Reduction
M Safaryan, A Peste, D Alistarh
Advances in Neural Information Processing Systems (NeurIPS) 2023, 2023
32023
LDAdam: Adaptive Optimization from Low-dimensional Gradient Statistics
T Robert, M Safaryan, IV Modoranu, D Alistarh
International Conference on Learning Representations (ICLR), 2025, 2024
22024
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