Feature Distillation With Guided Adversarial Contrastive Learning

21 September 2020

Jun Zhao

Papers citing "Feature Distillation With Guided Adversarial Contrastive Learning"

48 / 48 papers shown

Title
CKD: Contrastive Knowledge Distillation from A Sample-wise Perspective Wencheng Zhu Xin Zhou Pengfei Zhu Yu Wang Qinghua Hu VLM 92 1 0 22 Apr 2024
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 151 30,069 0 01 Mar 2022
What Makes for Good Views for Contrastive Learning? Yonglong Tian Chen Sun Ben Poole Dilip Krishnan Cordelia Schmid Phillip Isola SSL 75 1,313 0 20 May 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 59 149 0 20 May 2020
Deflecting Adversarial Attacks Yao Qin Nicholas Frosst Colin Raffel G. Cottrell Geoffrey E. Hinton AAML 48 16 0 18 Feb 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 255 18,607 0 13 Feb 2020
Momentum Contrast for Unsupervised Visual Representation Learning Kaiming He Haoqi Fan Yuxin Wu Saining Xie Ross B. Girshick SSL 113 12,007 0 13 Nov 2019
Contrastive Representation Distillation Yonglong Tian Dilip Krishnan Phillip Isola 98 1,042 0 23 Oct 2019
Adversarial Learning with Margin-based Triplet Embedding Regularization Yaoyao Zhong Weihong Deng AAML 64 50 0 20 Sep 2019
Sparse and Imperceivable Adversarial Attacks Francesco Croce Matthias Hein AAML 65 199 0 11 Sep 2019
Metric Learning for Adversarial Robustness Chengzhi Mao Ziyuan Zhong Junfeng Yang Carl Vondrick Baishakhi Ray OOD 55 185 0 03 Sep 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 57 230 0 24 Jul 2019
Adversarial Robustness through Local Linearization Chongli Qin James Martens Sven Gowal Dilip Krishnan Krishnamurthy Dvijotham Alhussein Fawzi Soham De Robert Stanforth Pushmeet Kohli AAML 56 307 0 04 Jul 2019
Contrastive Multiview Coding Yonglong Tian Dilip Krishnan Phillip Isola SSL 131 2,385 0 13 Jun 2019
Adversarially Robust Distillation Micah Goldblum Liam H. Fowl Soheil Feizi Tom Goldstein AAML 36 204 0 23 May 2019
Adversarially robust transfer learning Ali Shafahi Parsa Saadatpanah Chen Zhu Amin Ghiasi Christoph Studer David Jacobs Tom Goldstein OOD 25 116 0 20 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 50 852 0 17 May 2019
On Variational Bounds of Mutual Information Ben Poole Sherjil Ozair Aaron van den Oord Alexander A. Alemi George Tucker SSL 65 802 0 16 May 2019
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 107 1,238 0 29 Apr 2019
Relational Knowledge Distillation Wonpyo Park Dongju Kim Yan Lu Minsu Cho 54 1,396 0 10 Apr 2019
A Comprehensive Overhaul of Feature Distillation Byeongho Heo Jeesoo Kim Sangdoo Yun Hyojin Park Nojun Kwak J. Choi 61 571 0 03 Apr 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 62 726 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 96 2,525 0 24 Jan 2019
Feature Denoising for Improving Adversarial Robustness Cihang Xie Yuxin Wu Laurens van der Maaten Alan Yuille Kaiming He 78 907 0 09 Dec 2018
SparseFool: a few pixels make a big difference Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 30 197 0 06 Nov 2018
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models D. Su Huan Zhang Hongge Chen Jinfeng Yi Pin-Yu Chen Yupeng Gao VLM 87 390 0 05 Aug 2018
Representation Learning with Contrastive Predictive Coding Aaron van den Oord Yazhe Li Oriol Vinyals DRL SSL 229 10,152 0 10 Jul 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 80 1,772 0 30 May 2018
Towards the first adversarially robust neural network model on MNIST Lukas Schott Jonas Rauber Matthias Bethge Wieland Brendel AAML OOD 43 369 0 23 May 2018
Adversarial Logit Pairing Harini Kannan Alexey Kurakin Ian Goodfellow AAML 75 627 0 16 Mar 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 161 3,171 0 01 Feb 2018
Deflecting Adversarial Attacks with Pixel Deflection Aaditya (Adi) Prakash N. Moran Solomon Garber Antonella DiLillo J. Storer AAML 45 302 0 26 Jan 2018
Defense against Adversarial Attacks Using High-Level Representation Guided Denoiser Fangzhou Liao Ming Liang Yinpeng Dong Tianyu Pang Xiaolin Hu Jun Zhu 76 879 0 08 Dec 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 229 11,962 0 19 Jun 2017
Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction Richard Y. Zhang Phillip Isola Alexei A. Efros SSL DRL 51 667 0 29 Nov 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 170 8,513 0 16 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 494 5,878 0 08 Jul 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 268 7,951 0 23 May 2016
Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles M. Noroozi Paolo Favaro SSL 135 2,973 0 30 Mar 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 49 3,660 0 08 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.4K 192,638 0 10 Dec 2015
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 66 3,947 0 24 Nov 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 45 3,061 0 14 Nov 2015
Unsupervised Visual Representation Learning by Context Prediction Carl Doersch Abhinav Gupta Alexei A. Efros DRL SSL 153 2,777 0 19 May 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 238 19,523 0 09 Mar 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 176 18,922 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 185 14,831 1 21 Dec 2013
Distributed Representations of Words and Phrases and their Compositionality Tomas Mikolov Ilya Sutskever Kai Chen G. Corrado J. Dean NAI OCL 300 33,445 0 16 Oct 2013