Augment your batch: better training with larger batches

27 January 2019

Papers citing "Augment your batch: better training with larger batches"

24 / 24 papers shown

Title
LookHere: Vision Transformers with Directed Attention Generalize and Extrapolate A. Fuller Daniel G. Kyrollos Yousef Yassin James R. Green 52 2 0 22 May 2024
Poly-View Contrastive Learning Amitis Shidani Devon Hjelm Jason Ramapuram Russ Webb Eeshan Gunesh Dhekane Dan Busbridge VLM SSL 34 4 0 08 Mar 2024
Differentially Private Image Classification by Learning Priors from Random Processes Xinyu Tang Ashwinee Panda Vikash Sehwag Prateek Mittal 23 20 0 08 Jun 2023
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization Ashwinee Panda Xinyu Tang Saeed Mahloujifar Vikash Sehwag Prateek Mittal 43 11 0 08 Dec 2022
Adaptive scaling of the learning rate by second order automatic differentiation F. Gournay Alban Gossard ODL 28 1 0 26 Oct 2022
R-MelNet: Reduced Mel-Spectral Modeling for Neural TTS Kyle Kastner Aaron Courville 32 0 0 30 Jun 2022
CVNets: High Performance Library for Computer Vision Sachin Mehta Farzad Abdolhosseini Mohammad Rastegari 29 18 0 04 Jun 2022
Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks C. F. G. Santos João Paulo Papa 30 211 0 10 Jan 2022
AutoFormer: Searching Transformers for Visual Recognition Minghao Chen Houwen Peng Jianlong Fu Haibin Ling ViT 36 259 0 01 Jul 2021
Early Convolutions Help Transformers See Better Tete Xiao Mannat Singh Eric Mintun Trevor Darrell Piotr Dollár Ross B. Girshick 20 753 0 28 Jun 2021
Data augmentation in Bayesian neural networks and the cold posterior effect Seth Nabarro Stoil Ganev Adrià Garriga-Alonso Vincent Fortuin Mark van der Wilk Laurence Aitchison BDL 29 37 0 10 Jun 2021
Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead Maurizio Capra Beatrice Bussolino Alberto Marchisio Guido Masera Maurizio Martina Muhammad Shafique BDL 59 140 0 21 Dec 2020
Learning Loss for Test-Time Augmentation Ildoo Kim Younghoon Kim Sungwoong Kim OOD 20 90 0 22 Oct 2020
Improved generalization by noise enhancement Takashi Mori Masahito Ueda 21 3 0 28 Sep 2020
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 34 79 0 17 Sep 2020
UniformAugment: A Search-free Probabilistic Data Augmentation Approach Tom Ching LingChen Ava Khonsari Amirreza Lashkari M. Nazari Jaspreet Singh Sambee M. Nascimento 19 58 0 31 Mar 2020
Topologically Densified Distributions Christoph Hofer Florian Graf Marc Niethammer Roland Kwitt 27 15 0 12 Feb 2020
Learning by Cheating Dian Chen Brady Zhou V. Koltun Philipp Krahenbuhl SSL 47 503 0 27 Dec 2019
Adversarial AutoAugment Xinyu Zhang Qiang-qiang Wang Jian Zhang Zhaobai Zhong AAML 28 196 0 24 Dec 2019
Occlusions for Effective Data Augmentation in Image Classification Ruth C. Fong Andrea Vedaldi 24 20 0 23 Oct 2019
Faster Neural Network Training with Data Echoing Dami Choi Alexandre Passos Christopher J. Shallue George E. Dahl 20 48 0 12 Jul 2019
MultiGrain: a unified image embedding for classes and instances Maxim Berman Hervé Jégou Andrea Vedaldi Iasonas Kokkinos Matthijs Douze 15 110 0 14 Feb 2019
RenderGAN: Generating Realistic Labeled Data Leon Sixt Benjamin Wild Tim Landgraf GAN 158 176 0 04 Nov 2016
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