At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima
Selection in Asynchronous Training of Neural Networks?

At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks?

26 September 2019

Mor Shpigel Nacson

Papers citing "At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks?"

10 / 10 papers shown

Title
Ordered Momentum for Asynchronous SGD Chang-Wei Shi Yi-Rui Yang Wu-Jun Li ODL 62 0 0 27 Jul 2024
DropCompute: simple and more robust distributed synchronous training via compute variance reduction Niv Giladi Shahar Gottlieb Moran Shkolnik A. Karnieli Ron Banner Elad Hoffer Kfir Y. Levy Daniel Soudry 38 2 0 18 Jun 2023
TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training Tuo Zhang Lei Gao Sunwoo Lee Mi Zhang Salman Avestimehr FedML 34 28 0 14 Apr 2023
DoCoFL: Downlink Compression for Cross-Device Federated Learning Ron Dorfman S. Vargaftik Y. Ben-Itzhak Kfir Y. Levy FedML 32 19 0 01 Feb 2023
Second-order regression models exhibit progressive sharpening to the edge of stability Atish Agarwala Fabian Pedregosa Jeffrey Pennington 35 26 0 10 Oct 2022
Beyond the Quadratic Approximation: the Multiscale Structure of Neural Network Loss Landscapes Chao Ma D. Kunin Lei Wu Lexing Ying 25 27 0 24 Apr 2022
Stochastic Training is Not Necessary for Generalization Jonas Geiping Micah Goldblum Phillip E. Pope Michael Moeller Tom Goldstein 89 72 0 29 Sep 2021
DBS: Dynamic Batch Size For Distributed Deep Neural Network Training Qing Ye Yuhao Zhou Mingjia Shi Yanan Sun Jiancheng Lv 22 11 0 23 Jul 2020
Pipelined Backpropagation at Scale: Training Large Models without Batches Atli Kosson Vitaliy Chiley Abhinav Venigalla Joel Hestness Urs Koster 35 33 0 25 Mar 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 308 2,890 0 15 Sep 2016