Παρακολούθηση
Abdurakhmon Sadiev
Abdurakhmon Sadiev
PhD student, KAUST
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα kaust.edu.sa
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
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
472023
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
422020
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
352022
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
332021
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
282021
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
27*2024
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
202022
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
19*2022
AI-SARAH: Adaptive and implicit stochastic recursive gradient methods
Z Shi, A Sadiev, N Loizou, P Richtárik, M Takáč
142023
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
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
102023
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
92024
Adaptive compression for communication-efficient distributed training
M Makarenko, E Gasanov, R Islamov, A Sadiev, P Richtárik
arXiv preprint arXiv:2211.00188, 2022
82022
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
42024
A Unified Theory of Stochastic Proximal Point Methods without Smoothness
P Richtárik, A Sadiev, Y Demidovich
arXiv preprint arXiv:2405.15941, 2024
32024
Stochastic proximal point methods for monotone inclusions under expected similarity
A Sadiev, L Condat, P Richtárik
arXiv preprint arXiv:2405.14255, 2024
32024
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
12022
Differentially Private Random Block Coordinate Descent
A Maranjyan, A Sadiev, P Richtárik
arXiv preprint arXiv:2412.17054, 2024
2024
Error Feedback under -Smoothness: Normalization and Momentum
S Khirirat, A Sadiev, A Riabinin, E Gorbunov, P Richtárik
arXiv preprint arXiv:2410.16871, 2024
2024
Communication-efficient Algorithms Under Generalized Smoothness Assumptions
S Khirirat, A Sadiev, A Riabinin, E Gorbunov, P Richtárik
OPT 2024: Optimization for Machine Learning, 0
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