On Empirical Comparisons of Optimizers for Deep Learning

11 October 2019

Papers citing "On Empirical Comparisons of Optimizers for Deep Learning"

5 / 105 papers shown

Title
Individual predictions matter: Assessing the effect of data ordering in training fine-tuned CNNs for medical imaging J. Zech Jessica Zosa Forde Michael L. Littman 23 5 0 08 Dec 2019
Optimizer Benchmarking Needs to Account for Hyperparameter Tuning Prabhu Teja Sivaprasad Florian Mai Thijs Vogels Martin Jaggi François Fleuret 22 12 0 25 Oct 2019
Demon: Improved Neural Network Training with Momentum Decay John Chen Cameron R. Wolfe Zhaoqi Li Anastasios Kyrillidis ODL 24 15 0 11 Oct 2019
Quasi-hyperbolic momentum and Adam for deep learning Jerry Ma Denis Yarats ODL 84 129 0 16 Oct 2018
A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay L. Smith 208 1,020 0 26 Mar 2018