Adversarial Training Helps Transfer Learning via Better Representations

18 June 2021

Papers citing "Adversarial Training Helps Transfer Learning via Better Representations"

49 / 49 papers shown

Title
No Query, No Access Wenjie Wang Siyuan Liang Yize Zhang Xiaojun Jia Hao Lin Xiaochun Cao AAML 57 1 0 12 May 2025
Controlled Training Data Generation with Diffusion Models Teresa Yeo Andrei Atanov Harold Benoit Aleksandr Alekseev Ruchira Ray Pooya Esmaeil Akhoondi Amir Zamir 73 6 0 22 Mar 2024
Meta-Learning with Fewer Tasks through Task Interpolation Huaxiu Yao Linjun Zhang Chelsea Finn 76 56 0 04 Jun 2021
A Systematic Evaluation of Transfer Learning and Pseudo-labeling with BERT-based Ranking Models Iurii Mokrii Leonid Boytsov Pavel Braslavski 44 26 0 04 Mar 2021
Towards Understanding the Dynamics of the First-Order Adversaries Zhun Deng Hangfeng He Jiaoyang Huang Weijie J. Su AAML 39 11 0 20 Oct 2020
How Does Mixup Help With Robustness and Generalization? Linjun Zhang Zhun Deng Kenji Kawaguchi Amirata Ghorbani James Zou AAML 73 250 0 09 Oct 2020
Interpreting Robust Optimization via Adversarial Influence Functions Zhun Deng Cynthia Dwork Jialiang Wang Linjun Zhang TDI 16 12 0 03 Oct 2020
Improving Generalization in Meta-learning via Task Augmentation Huaxiu Yao Long-Kai Huang Linjun Zhang Ying Wei Li Tian James Zou Junzhou Huang Z. Li 80 83 0 26 Jul 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor Aleksander Madry 62 424 0 16 Jul 2020
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification Francisco Utrera Evan Kravitz N. Benjamin Erichson Rekha Khanna Michael W. Mahoney GAN 47 33 0 11 Jul 2020
On the Theory of Transfer Learning: The Importance of Task Diversity Nilesh Tripuraneni Michael I. Jordan Chi Jin 100 219 0 20 Jun 2020
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data Zhun Deng Linjun Zhang Amirata Ghorbani James Zou 64 32 0 15 Jun 2020
Enhancing Certified Robustness via Smoothed Weighted Ensembling Chizhou Liu Yunzhen Feng Ranran Wang Bin Dong AAML 33 12 0 19 May 2020
Certified Defenses for Adversarial Patches Ping Yeh-Chiang Renkun Ni Ahmed Abdelkader Chen Zhu Christoph Studer Tom Goldstein AAML 39 171 0 14 Mar 2020
Provable Meta-Learning of Linear Representations Nilesh Tripuraneni Chi Jin Michael I. Jordan OOD 96 191 0 26 Feb 2020
Few-Shot Learning via Learning the Representation, Provably S. Du Wei Hu Sham Kakade Jason D. Lee Qi Lei SSL 46 260 0 21 Feb 2020
Big Transfer (BiT): General Visual Representation Learning Alexander Kolesnikov Lucas Beyer Xiaohua Zhai J. Puigcerver Jessica Yung Sylvain Gelly N. Houlsby MQ 276 1,205 0 24 Dec 2019
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets Yogesh Balaji Tom Goldstein Judy Hoffman AAML 174 103 0 17 Oct 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 121 752 0 31 May 2019
Are Labels Required for Improving Adversarial Robustness? J. Uesato Jean-Baptiste Alayrac Po-Sen Huang Robert Stanforth Alhussein Fawzi Pushmeet Kohli AAML 71 333 0 31 May 2019
MixMatch: A Holistic Approach to Semi-Supervised Learning David Berthelot Nicholas Carlini Ian Goodfellow Nicolas Papernot Avital Oliver Colin Raffel 140 3,024 0 06 May 2019
Transfusion: Understanding Transfer Learning for Medical Imaging M. Raghu Chiyuan Zhang Jon M. Kleinberg Samy Bengio MedIm 77 983 0 14 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 130 2,036 0 08 Feb 2019
Parameter-Efficient Transfer Learning for NLP N. Houlsby A. Giurgiu Stanislaw Jastrzebski Bruna Morrone Quentin de Laroussilhe Andrea Gesmundo Mona Attariyan Sylvain Gelly 208 4,449 0 02 Feb 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 69 727 0 28 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 129 2,548 0 24 Jan 2019
When Semi-Supervised Learning Meets Transfer Learning: Training Strategies, Models and Datasets Hong-Yu Zhou Avital Oliver Jianxin Wu Yefeng Zheng 43 22 0 13 Dec 2018
Adversarially Robust Generalization Requires More Data Ludwig Schmidt Shibani Santurkar Dimitris Tsipras Kunal Talwar Aleksander Madry OOD AAML 131 790 0 30 Apr 2018
SentEval: An Evaluation Toolkit for Universal Sentence Representations Alexis Conneau Douwe Kiela 92 639 0 14 Mar 2018
Certified Robustness to Adversarial Examples with Differential Privacy Mathias Lécuyer Vaggelis Atlidakis Roxana Geambasu Daniel J. Hsu Suman Jana SILM AAML 92 932 0 09 Feb 2018
Certified Defenses against Adversarial Examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 105 968 0 29 Jan 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 116 1,409 0 08 Dec 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 287 12,060 0 19 Jun 2017
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning Takeru Miyato S. Maeda Masanori Koyama S. Ishii GAN 146 2,733 0 13 Apr 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 467 3,140 0 04 Nov 2016
What makes ImageNet good for transfer learning? Minyoung Huh Pulkit Agrawal Alexei A. Efros OOD SSeg VLM SSL 102 676 0 30 Aug 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 247 8,550 0 16 Aug 2016
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning Hoo-Chang Shin H. Roth Mingchen Gao Le Lu Ziyue Xu Isabella Nogues Jianhua Yao D. Mollura Ronald M. Summers 58 4,602 0 10 Feb 2016
False Discoveries Occur Early on the Lasso Path Weijie Su M. Bogdan Emmanuel Candes 159 181 0 05 Nov 2015
The Benefit of Multitask Representation Learning Andreas Maurer Massimiliano Pontil Bernardino Romera-Paredes SSL 102 375 0 23 May 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 254 19,045 0 20 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 155 3,271 0 05 Dec 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.6K 39,509 0 01 Sep 2014
A useful variant of the Davis--Kahan theorem for statisticians Yi Yu Tengyao Wang R. Samworth 92 577 0 04 May 2014
CNN Features off-the-shelf: an Astounding Baseline for Recognition A. Razavian Hossein Azizpour Josephine Sullivan S. Carlsson 149 4,939 0 23 Mar 2014
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition Jeff Donahue Yangqing Jia Oriol Vinyals Judy Hoffman Ning Zhang Eric Tzeng Trevor Darrell VLM ObjD 176 4,949 0 06 Oct 2013
Fine-Grained Visual Classification of Aircraft Subhransu Maji Esa Rahtu Arno Solin Matthew Blaschko Andrea Vedaldi 109 2,257 0 21 Jun 2013
A Model of Inductive Bias Learning Jonathan Baxter 103 1,213 0 01 Jun 2011
The LASSO risk for gaussian matrices Mohsen Bayati Andrea Montanari 186 318 0 16 Aug 2010