3 citations · 3 across the 3 of their papers we have counts for
3 papers
Communication-Efficient Federated Learning with Adaptive Number of Participants
Sergey Skorik, Vladislav Dorofeev, Gleb Molodtsov +4
Rapid scaling of deep learning models has enabled performance gains across domains, yet it introduced several challenges. Federated Learning (FL) has emerged as a promising framewo…
Effective Method with Compression for Distributed and Federated Cocoercive Variational Inequalities
Daniil Medyakov, Gleb Molodtsov, Aleksandr Beznosikov
Variational inequalities as an effective tool for solving applied problems, including machine learning tasks, have been attracting more and more attention from researchers in recen…
Optimal Data Splitting in Distributed Optimization for Machine Learning
Daniil Medyakov, Gleb Molodtsov, Aleksandr Beznosikov +1
The distributed optimization problem has become increasingly relevant recently. It has a lot of advantages such as processing a large amount of data in less time compared to non-di…