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math.OC2024
A Simple Linear Convergence Analysis of the Point-SAGA Algorithm
Laurent Condat, Peter Richtárik
Point-SAGA is a randomized algorithm for minimizing a sum of convex functions using their proximity operators (proxs), proposed by Defazio (2016). At every iteration, the prox of o…
math.OC2024
Stochastic Proximal Point Methods for Monotone Inclusions under Expected Similarity
Abdurakhmon Sadiev, Laurent Condat, Peter Richtárik
Monotone inclusions have a wide range of applications, including minimization, saddle-point, and equilibria problems. We introduce new stochastic algorithms, with or without varian…
cs.LG2024
Sparse-ProxSkip: Accelerated Sparse-to-Sparse Training in Federated Learning
Georg Meinhardt, Kai Yi, Laurent Condat +1
In Federated Learning (FL), both client resource constraints and communication costs pose major problems for training large models. In the centralized setting, sparse training addr…