Improved asynchronous parallel optimization analysis for stochastic incremental methods

11 January 2018

Papers citing "Improved asynchronous parallel optimization analysis for stochastic incremental methods"

15 / 15 papers shown

Title
Faster Stochastic Optimization with Arbitrary Delays via Asynchronous Mini-Batching Amit Attia Ofir Gaash Tomer Koren 40 0 0 14 Aug 2024
Asynchronous Federated Learning with Bidirectional Quantized Communications and Buffered Aggregation Tomàs Ortega Hamid Jafarkhani FedML 38 6 0 01 Aug 2023
Layer-wise Adaptive Step-Sizes for Stochastic First-Order Methods for Deep Learning Achraf Bahamou D. Goldfarb ODL 36 0 0 23 May 2023
Delay-adaptive step-sizes for asynchronous learning Xuyang Wu Sindri Magnússon Hamid Reza Feyzmahdavian M. Johansson 32 14 0 17 Feb 2022
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization Kaiwen Zhou Anthony Man-Cho So James Cheng 32 1 0 30 Sep 2021
Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes Marten van Dijk Nhuong V. Nguyen Toan N. Nguyen Lam M. Nguyen Quoc Tran-Dinh Phuong Ha Nguyen FedML 42 10 0 27 Oct 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 42 0 0 26 Aug 2020
Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise Marten van Dijk Nhuong V. Nguyen Toan N. Nguyen Lam M. Nguyen Quoc Tran-Dinh Phuong Ha Nguyen FedML 21 28 0 17 Jul 2020
Robust Aggregation for Federated Learning Krishna Pillutla Sham Kakade Zaïd Harchaoui FedML 42 632 0 31 Dec 2019
The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Communication Sebastian U. Stich Sai Praneeth Karimireddy FedML 25 20 0 11 Sep 2019
Reducing Noise in GAN Training with Variance Reduced Extragradient Tatjana Chavdarova Gauthier Gidel François Fleuret Simon Lacoste-Julien 25 135 0 18 Apr 2019
Decoupled Greedy Learning of CNNs Eugene Belilovsky Michael Eickenberg Edouard Oyallon 14 115 0 23 Jan 2019
New Convergence Aspects of Stochastic Gradient Algorithms Lam M. Nguyen Phuong Ha Nguyen Peter Richtárik K. Scheinberg Martin Takáč Marten van Dijk 33 66 0 10 Nov 2018
A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates Yossi Arjevani Ohad Shamir Nathan Srebro 16 63 0 26 Jun 2018
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption Lam M. Nguyen Phuong Ha Nguyen Marten van Dijk Peter Richtárik K. Scheinberg Martin Takáč 47 226 0 11 Feb 2018