Mher Safaryan

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Peter RichtarikProfessor, KAUSTVerified email at kaust.edu.sa
Rustem IslamovPhD student, University of BaselVerified email at unibas.ch
Xun QianResearcher, Shanghai AI LabVerified email at pjlab.org.cn
Samuel HorvathMohamed bin Zayed University of Artificial Intelligence (MBZUAI)Verified email at mbzuai.ac.ae
Aleksandr BeznosikovPhD, Moscow Institute of Physics and TechnologyVerified email at phystech.edu
Sergey Davidovassociate professor, Yerevan State UniversityVerified email at ysu.am
Grigori KaragulyanInstitute of Mathematics, Armenian National Academy of SciencesVerified email at ysu.am
Filip HanzelyVerified email at kaust.edu.sa
Laurent CondatSenior Research Scientist, King Abdullah University of Science and Technology (KAUST), Saudi ArabiaVerified email at kaust.edu.sa
Egor ShulginPhD candidate, KAUSTVerified email at kaust.edu.sa
Dan AlistarhIST AustriaVerified email at ist.ac.at
Slavomír HanzelyPhD Candidate, KAUSTVerified email at kaust.edu.sa
Arto MaranjyanPhD student, King Abdullah University of Science and Technology (KAUST)Verified email at kaust.edu.sa
Davit KaragulyanPhD in mathemtics, KTH Royal Institute of MathematicsVerified email at kth.se
Diogo Aguiar GomesKing Abdullah University of Science and TechnologyVerified email at kaust.edu.sa
Mohammed SayyariOld Dominion UniversityVerified email at kaust.edu.sa
Vahagn AslanyanDKO Fellow, University of ManchesterVerified email at manchester.ac.uk
Ricardo de Lima RibeiroKAUSTVerified email at kaust.edu.sa
Alexandra PesteInstitute of Science and Technology AustriaVerified email at ist.ac.at
Eldar KurticIST AustriaVerified email at ist.ac.at

Mher Safaryan

Postdoctoral MSCA Fellow, IST Austria

Verified email at ist.ac.at - Homepage

Optimization Theory Machine Learning Harmonic Analysis


Title Sort by citations Sort by year Sort by 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	160	2020
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	72	2021
Optimal gradient compression for distributed and federated learning A Albasyoni, M Safaryan, L Condat, P Richtárik arXiv preprint arXiv:2010.03246, 2020	53	2020
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	52	2020
Stochastic Sign Descent Methods: New Algorithms and Better Theory M Safaryan, P Richtárik International Conference on Machine Learning (ICML), 2021, 2019	47*	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	25	2021
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	20	2021
Construction of free g-dimonoids Y Movsisyan, S Davidov, M Safaryan Algebra and discrete mathematics, 2014	16	2014
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	12*	2021
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	10	2015
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	9	2022
Gradskip: Communication-accelerated local gradient methods with better computational complexity A Maranjyan, M Safaryan, P Richtárik arXiv preprint arXiv:2210.16402, 2022	8	2022
On a theorem of Littlewood GA Karagulyan, MH Safaryan Hokkaido Mathematical Journal 46 (1), 87-106, 2017	6	2017
On an equivalence for differentiation bases of dyadic rectangles GA Karagulyan, DA Karagulyan, MH Safaryan Colloq. Math 146 (2), 295-307, 2017	6	2017
AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms R Islamov, M Safaryan, D Alistarh International Conference on Artificial Intelligence and Statistics (AISTATS …, 2023	5	2023
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	4	2021
On an equivalency of rare differentiation bases of rectangles MH Safaryan Journal of Contemporary Mathematical Analysis (Armenian Academy of Sciences …, 2018	4	2018
MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence IV Modoranu, M Safaryan, G Malinovsky, E Kurtic, T Robert, P Richtarik, ... arXiv preprint arXiv:2405.15593, 2024		2024
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

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