High-probability bounds for stochastic optimization and variational inequalities: the case of unbounded variance A Sadiev, M Danilova, E Gorbunov, S Horváth, G Gidel, P Dvurechensky, ...
International Conference on Machine Learning, 29563-29648, 2023
53 2023 Gradient-free methods with inexact oracle for convex-concave stochastic saddle-point problem A Beznosikov, A Sadiev, A Gasnikov
International Conference on Mathematical Optimization Theory and Operations …, 2020
42 2020 Optimal algorithms for decentralized stochastic variational inequalities D Kovalev, A Beznosikov, A Sadiev, M Persiianov, P Richtárik, ...
Advances in Neural Information Processing Systems 35, 31073-31088, 2022
35 2022 Solving smooth min-min and min-max problems by mixed oracle algorithms E Gladin, A Sadiev, A Gasnikov, P Dvurechensky, A Beznosikov, ...
International Conference on Mathematical Optimization Theory and Operations …, 2021
33 2021 Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences A Sadiev, G Malinovsky, E Gorbunov, I Sokolov, A Khaled, ...
The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
28 * 2024 Zeroth-order algorithms for smooth saddle-point problems A Sadiev, A Beznosikov, P Dvurechensky, A Gasnikov
International Conference on Mathematical Optimization Theory and Operations …, 2021
28 2021 Communication acceleration of local gradient methods via an accelerated primal-dual algorithm with an inexact prox A Sadiev, D Kovalev, P Richtárik
Advances in Neural Information Processing Systems 35, 21777-21791, 2022
21 2022 Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes A Sadiev, E Borodich, A Beznosikov, D Dvinskikh, S Chezhegov, ...
EURO Journal on Computational Optimization 10, 100041, 2022
21 * 2022 AI-SARAH: Adaptive and implicit stochastic recursive gradient methods Z Shi, A Sadiev, N Loizou, P Richtárik, M Takáč
14 2023 High-probability convergence for composite and distributed stochastic minimization and variational inequalities with heavy-tailed noise E Gorbunov, A Sadiev, M Danilova, S Horváth, G Gidel, P Dvurechensky, ...
arXiv preprint arXiv:2310.01860, 2023
11 2023 Decentralized personalized federated min-max problems E Borodich, A Beznosikov, A Sadiev, V Sushko, N Savelyev, M Takáč, ...
arXiv preprint arXiv:2106.07289, 2021
11 * 2021 Adaptive compression for communication-efficient distributed training M Makarenko, E Gasanov, R Islamov, A Sadiev, P Richtárik
arXiv preprint arXiv:2211.00188, 2022
10 2022 Stochastic gradient methods with preconditioned updates A Sadiev, A Beznosikov, AJ Almansoori, D Kamzolov, R Tappenden, ...
Journal of Optimization Theory and Applications 201 (2), 471-489, 2024
9 2024 A Unified Theory of Stochastic Proximal Point Methods without Smoothness P Richtárik, A Sadiev, Y Demidovich
arXiv preprint arXiv:2405.15941, 2024
5 2024 SPAM: Stochastic Proximal Point Method with Momentum Variance Reduction for Non-convex Cross-Device Federated Learning A Karagulyan, E Shulgin, A Sadiev, P Richtárik
arXiv preprint arXiv:2405.20127, 2024
4 2024 Stochastic proximal point methods for monotone inclusions under expected similarity A Sadiev, L Condat, P Richtárik
arXiv preprint arXiv:2405.14255, 2024
4 2024 Error Feedback under S Khirirat, A Sadiev, A Riabinin, E Gorbunov, P Richtárik
arXiv preprint arXiv:2410.16871, 2024
2 * 2024 An Approach for Non-convex Uniformly Concave Structured Saddle Point Problem M Alkousa, A Gasnikov, P Dvurechensky, A Sadiev, L Razouk
arXiv preprint arXiv:2202.06376, 2022
1 2022 Differentially Private Random Block Coordinate Descent A Maranjyan, A Sadiev, P Richtárik
arXiv preprint arXiv:2412.17054, 2024
2024 
Peter RichtarikProfessor, KAUSTEmail verificata su kaust.edu.sa
