v1v2 (latest)

General Cyclical Training of Neural Networks

17 February 2022

Papers citing "General Cyclical Training of Neural Networks"

34 / 34 papers shown

Title
Cyclical Focal Loss L. Smith 60 14 0 16 Feb 2022
Automated Deep Learning: Neural Architecture Search Is Not the End Xuanyi Dong D. Kedziora Katarzyna Musial Bogdan Gabrys 117 27 0 16 Dec 2021
A survey on multi-objective hyperparameter optimization algorithms for Machine Learning A. Hernández I. Nieuwenhuyse Sebastian Rojas Gonzalez 72 103 0 23 Nov 2021
Which Samples Should be Learned First: Easy or Hard? Xiaoling Zhou Ou Wu 69 17 0 11 Oct 2021
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO Katharina Eggensperger Philip Muller Neeratyoy Mallik Matthias Feurer René Sass Aaron Klein Noor H. Awad Marius Lindauer Frank Hutter 221 104 0 14 Sep 2021
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges B. Bischl Martin Binder Michel Lang Tobias Pielok Jakob Richter ... Theresa Ullmann Marc Becker A. Boulesteix Difan Deng Marius Lindauer 245 503 0 13 Jul 2021
A Survey on Data Augmentation for Text Classification Markus Bayer M. Kaufhold Christian A. Reuter 145 354 0 07 Jul 2021
Understanding Decoupled and Early Weight Decay Johan Bjorck Kilian Q. Weinberger Carla P. Gomes 52 25 0 27 Dec 2020
Building One-Shot Semi-supervised (BOSS) Learning up to Fully Supervised Performance L. Smith A. Conovaloff SSL 62 8 0 16 Jun 2020
On the training dynamics of deep networks with $L_2$ regularization Aitor Lewkowycz Guy Gur-Ari 96 54 0 15 Jun 2020
TResNet: High Performance GPU-Dedicated Architecture T. Ridnik Hussam Lawen Asaf Noy Emanuel Ben-Baruch Gilad Sharir Itamar Friedman OOD 97 214 0 30 Mar 2020
The Early Phase of Neural Network Training Jonathan Frankle D. Schwab Ari S. Morcos 89 174 0 24 Feb 2020
Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments Rémy Portelas Cédric Colas Katja Hofmann Pierre-Yves Oudeyer 68 146 0 16 Oct 2019
RandAugment: Practical automated data augmentation with a reduced search space E. D. Cubuk Barret Zoph Jonathon Shlens Quoc V. Le MQ 273 3,508 0 30 Sep 2019
Adaptive Weight Decay for Deep Neural Networks Kensuke Nakamura Byung-Woo Hong 58 43 0 21 Jul 2019
Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence Aditya Golatkar Alessandro Achille Stefano Soatto 80 97 0 30 May 2019
Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation Linfeng Zhang Jiebo Song Anni Gao Jingwei Chen Chenglong Bao Kaisheng Ma FedML 76 865 0 17 May 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 196 3,458 0 28 Mar 2019
Three Mechanisms of Weight Decay Regularization Guodong Zhang Chaoqi Wang Bowen Xu Roger C. Grosse 75 259 0 29 Oct 2018
AutoAugment: Learning Augmentation Policies from Data E. D. Cubuk Barret Zoph Dandelion Mané Vijay Vasudevan Quoc V. Le 135 1,775 0 24 May 2018
Visualizing the Loss Landscape of Neural Nets Hao Li Zheng Xu Gavin Taylor Christoph Studer Tom Goldstein 266 1,901 0 28 Dec 2017
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels Lu Jiang Zhengyuan Zhou Thomas Leung Li Li Li Fei-Fei NoLa 133 1,459 0 14 Dec 2017
Don't Decay the Learning Rate, Increase the Batch Size Samuel L. Smith Pieter-Jan Kindermans Chris Ying Quoc V. Le ODL 117 996 0 01 Nov 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 316 9,815 0 25 Oct 2017
Improved Regularization of Convolutional Neural Networks with Cutout Terrance Devries Graham W. Taylor 137 3,775 0 15 Aug 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,877 0 14 Jun 2017
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour Priya Goyal Piotr Dollár Ross B. Girshick P. Noordhuis Lukasz Wesolowski Aapo Kyrola Andrew Tulloch Yangqing Jia Kaiming He 3DH 128 3,688 0 08 Jun 2017
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 352 8,190 0 13 Aug 2016
Gradual DropIn of Layers to Train Very Deep Neural Networks L. Smith Emily M. Hand T. Doster AI4CE 82 33 0 22 Nov 2015
Net2Net: Accelerating Learning via Knowledge Transfer Tianqi Chen Ian Goodfellow Jonathon Shlens 187 672 0 18 Nov 2015
Training Very Deep Networks R. Srivastava Klaus Greff Jürgen Schmidhuber 165 1,687 0 22 Jul 2015
Cyclical Learning Rates for Training Neural Networks L. Smith ODL 240 2,541 0 03 Jun 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 367 19,745 0 09 Mar 2015
FitNets: Hints for Thin Deep Nets Adriana Romero Nicolas Ballas Samira Ebrahimi Kahou Antoine Chassang C. Gatta Yoshua Bengio FedML 330 3,906 0 19 Dec 2014