MaxUp: A Simple Way to Improve Generalization of Neural Network Training

20 February 2020

Papers citing "MaxUp: A Simple Way to Improve Generalization of Neural Network Training"

39 / 39 papers shown

Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise RegularizationNeural Information Processing Systems (NeurIPS), 2024

Junlin He

Jinxiao Du

Susu Xu

Wei Ma

227

01 Nov 2024

Enhancing Code Vulnerability Detection via Vulnerability-Preserving Data Augmentation

248

15 Apr 2024

Distilling Out-of-Distribution Robustness from Vision-Language Foundation ModelsNeural Information Processing Systems (NeurIPS), 2023

Andy Zhou

312

02 Nov 2023

Hazards in Deep Learning Testing: Prevalence, Impact and Recommendations

Yuejun Guo

182

11 Sep 2023

Improving Generalization in Meta-Learning via Meta-Gradient AugmentationInternational Joint Conference on Artificial Intelligence (IJCAI), 2023

253

14 Jun 2023

GAT: Guided Adversarial Training with Pareto-optimal Auxiliary TasksInternational Conference on Machine Learning (ICML), 2023

284

06 Feb 2023

Run-Off Election: Improved Provable Defense against Data Poisoning AttacksInternational Conference on Machine Learning (ICML), 2023

Keivan Rezaei

Kiarash Banihashem

Atoosa Malemir Chegini

Soheil Feizi

AAML

498

05 Feb 2023

Accelerating Self-Supervised Learning via Efficient Training StrategiesIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2022

Mustafa Taha Koccyiugit

Timothy M. Hospedales

Hakan Bilen

SSL

189

11 Dec 2022

Data-free Backdoor Removal based on Channel LipschitznessEuropean Conference on Computer Vision (ECCV), 2022

356

133

05 Aug 2022

Removing Batch Normalization Boosts Adversarial TrainingInternational Conference on Machine Learning (ICML), 2022

260

04 Jul 2022

Boosting Factorization Machines via Saliency-Guided MixupIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022

Defu Lian

Enhong Chen

208

17 Jun 2022

Multi-Augmentation for Efficient Visual Representation Learning for Self-supervised Pre-training

164

24 May 2022

ALLSH: Active Learning Guided by Local Sensitivity and Hardness

Mingyuan Zhou

312

10 May 2022

Indiscriminate Data Poisoning Attacks on Neural Networks

302

19 Apr 2022

AugMax: Adversarial Composition of Random Augmentations for Robust Training

352

133

26 Oct 2021

On Hard Episodes in Meta-Learning

163

21 Oct 2021

Ortho-Shot: Low Displacement Rank Regularization with Data Augmentation for Few-Shot Learning

Uche M. Osahor

Nasser M. Nasrabadi

168

18 Oct 2021

425

05 Oct 2021

HCDG: A Hierarchical Consistency Framework for Domain Generalization on Medical Image Segmentation

Yijun Yang

Shujun Wang

Lei Zhu

Lequan Yu

344

13 Sep 2021

SanitAIs: Unsupervised Data Augmentation to Sanitize Trojaned Neural Networks

288

09 Sep 2021

Taxonomy of Machine Learning Safety: A Survey and PrimerACM Computing Surveys (CSUR), 2021

333

09 Jun 2021

Vision Transformers with Patch Diversification

317

26 Apr 2021

DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations

Furong Huang

420

02 Mar 2021

What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning

198

26 Feb 2021

Improving Robustness of Learning-based Autonomous Steering Using Adversarial Images

207

26 Feb 2021

On the Inherent Regularization Effects of Noise Injection During TrainingInternational Conference on Machine Learning (ICML), 2021

Oussama Dhifallah

Yue M. Lu

161

15 Feb 2021

High-Performance Large-Scale Image Recognition Without NormalizationInternational Conference on Machine Learning (ICML), 2021

577

602

11 Feb 2021

Generalising via Meta-Examples for Continual Learning in the WildInternational Conference on Machine Learning, Optimization, and Data Science (MOD), 2021

227

28 Jan 2021

Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and DefensesIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020

Chulin Xie

567

376

18 Dec 2020

KeepAugment: A Simple Information-Preserving Data Augmentation ApproachComputer Vision and Pattern Recognition (CVPR), 2020

191

140

23 Nov 2020

Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy TradeoffIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020

274

145

18 Nov 2020

AttentiveNAS: Improving Neural Architecture Search via Attentive SamplingComputer Vision and Pattern Recognition (CVPR), 2020

315

117

18 Nov 2020

Data Augmentation for Meta-Learning

276

14 Oct 2020

Encoding Robustness to Image Style via Adversarial Feature PerturbationsNeural Information Processing Systems (NeurIPS), 2020

Zuxuan Wu

211

18 Sep 2020

Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution

200

30 Jun 2020

Bootstrap your own latent: A new approach to self-supervised LearningNeural Information Processing Systems (NeurIPS), 2020

Pierre Harvey Richemond

...

Bilal Piot

1.7K

8,171

13 Jun 2020

Architectural Resilience to Foreground-and-Background Adversarial Noise

Carl Cheng

Evan Hu

AAML

161

23 Mar 2020

Smoothed Inference for Adversarially-Trained Models

Yaniv Nemcovsky

Evgenii Zheltonozhskii

179

17 Nov 2019

Diametrical Risk Minimization: Theory and ComputationsMachine-mediated learning (ML), 2019

Matthew Norton

Pratiksha Agrawal

371

24 Oct 2019