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communication efficiency 1data heterogeneity 1distributed learning 1local sgd 1optimization algorithms 1

From the 1 of 11 linked papers with an AI index.

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20242026
most citedThe Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication

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math.OC2025

Monotone and nonmonotone linearized block coordinate descent methods for nonsmooth composite optimization problems

Yassine Nabou, Lahcen El Bourkhissi, Sebastian U. Stich +1

In this paper, we introduce both monotone and nonmonotone variants of LiBCoD, a \textbf{Li}nearized \textbf{B}lock \textbf{Co}ordinate \textbf{D}escent method for solving composite…

math.OC2025

Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis

Ruichen Luo, Sebastian U Stich, Samuel Horváth +1

LocalSGD and SCAFFOLD are widely used methods in distributed stochastic optimization, with numerous applications in machine learning, large-scale data processing, and federated lea…

math.OC2024

Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates

Siqi Zhang, Sayantan Choudhury, Sebastian U Stich +1

Distributed and federated learning algorithms and techniques associated primarily with minimization problems. However, with the increase of minimax optimization and variational ine…