Sharper Rates and Flexible Framework for Nonconvex SGD with Client and Data Sampling

5 June 2022

Papers citing "Sharper Rates and Flexible Framework for Nonconvex SGD with Client and Data Sampling"

7 / 7 papers shown

Title
BurTorch: Revisiting Training from First Principles by Coupling Autodiff, Math Optimization, and Systems Konstantin Burlachenko Peter Richtárik AI4CE 71 0 0 18 Mar 2025
Tighter Performance Theory of FedExProx Wojciech Anyszka Kaja Gruntkowska Alexander Tyurin Peter Richtárik FedML 57 0 0 20 Oct 2024
SPAM: Stochastic Proximal Point Method with Momentum Variance Reduction for Non-convex Cross-Device Federated Learning Avetik G. Karagulyan Egor Shulgin Abdurakhmon Sadiev Peter Richtárik FedML 103 3 0 30 May 2024
Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations Alexander Tyurin Kaja Gruntkowska Peter Richtárik 82 3 0 24 May 2024
Correlated Quantization for Faster Nonconvex Distributed Optimization Andrei Panferov Yury Demidovich Ahmad Rammal Peter Richtárik MQ 122 4 0 10 Jan 2024
Improving Accelerated Federated Learning with Compression and Importance Sampling Michal Grudzieñ Grigory Malinovsky Peter Richtárik FedML 86 11 0 05 Jun 2023
Can 5th Generation Local Training Methods Support Client Sampling? Yes! Michal Grudzieñ Grigory Malinovsky Peter Richtárik 111 29 0 29 Dec 2022