Adversarially Robust Generalization Requires More Data

30 April 2018

Papers citing "Adversarially Robust Generalization Requires More Data"

50 / 198 papers shown

Title
A Light Recipe to Train Robust Vision Transformers Edoardo Debenedetti Vikash Sehwag Prateek Mittal ViT 32 69 0 15 Sep 2022
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization) Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos V. Cevher 44 19 0 15 Sep 2022
CelebV-HQ: A Large-Scale Video Facial Attributes Dataset Haoning Zhu Wayne Wu Wentao Zhu Liming Jiang Siwei Tang Li Zhang Ziwei Liu Chen Change Loy 62 155 0 25 Jul 2022
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness Chaoning Zhang Kang Zhang Chenshuang Zhang Axi Niu Jiu Feng Chang D. Yoo In So Kweon SSL 40 24 0 22 Jul 2022
AugRmixAT: A Data Processing and Training Method for Improving Multiple Robustness and Generalization Performance Xiaoliang Liu S. Furao Jian Zhao Changhai Nie AAML 15 1 0 21 Jul 2022
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations Tianlong Chen Peihao Wang Zhiwen Fan Zhangyang Wang 38 55 0 04 Jul 2022
On the Role of Generalization in Transferability of Adversarial Examples Yilin Wang Farzan Farnia AAML 24 10 0 18 Jun 2022
Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning Tianlong Chen Sijia Liu Shiyu Chang Lisa Amini Zhangyang Wang CLL 28 4 0 15 Jun 2022
Adversarial Reprogramming Revisited Matthias Englert R. Lazic AAML 29 9 0 07 Jun 2022
Robust Weight Perturbation for Adversarial Training Chaojian Yu Bo Han Biwei Huang Li Shen Shiming Ge Bo Du Tongliang Liu AAML 27 33 0 30 May 2022
Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction Ruochen Jiao Xiangguo Liu Takami Sato Qi Alfred Chen Qi Zhu AAML 43 20 0 27 May 2022
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power Binghui Li Jikai Jin Han Zhong J. Hopcroft Liwei Wang OOD 87 27 0 27 May 2022
Learn2Weight: Parameter Adaptation against Similar-domain Adversarial Attacks Siddhartha Datta AAML 38 4 0 15 May 2022
SETTI: A Self-supervised Adversarial Malware Detection Architecture in an IoT Environment Marjan Golmaryami R. Taheri Zahra Pooranian Mohammad Shojafar Pei Xiao 33 12 0 16 Apr 2022
A Simple Approach to Adversarial Robustness in Few-shot Image Classification Akshayvarun Subramanya Hamed Pirsiavash VLM 29 6 0 11 Apr 2022
SkeleVision: Towards Adversarial Resiliency of Person Tracking with Multi-Task Learning Nilaksh Das ShengYun Peng Duen Horng Chau AAML 35 2 0 02 Apr 2022
A Fast and Efficient Conditional Learning for Tunable Trade-Off between Accuracy and Robustness Souvik Kundu Sairam Sundaresan Massoud Pedram P. Beerel AAML 11 1 0 28 Mar 2022
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies Zhuang Qian Kaizhu Huang Qiufeng Wang Xu-Yao Zhang OOD AAML ObjD 54 72 0 26 Mar 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes Elvis Dohmatob A. Bietti AAML 39 13 0 22 Mar 2022
No Shifted Augmentations (NSA): compact distributions for robust self-supervised Anomaly Detection Mohamed Yousef Marcel R. Ackermann Unmesh Kurup Tom E. Bishop OODD OOD 45 3 0 19 Mar 2022
Why adversarial training can hurt robust accuracy Jacob Clarysse Julia Hörrmann Fanny Yang AAML 15 18 0 03 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 34 13 0 26 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang Min Lin Xiao Yang Junyi Zhu Shuicheng Yan 40 120 0 21 Feb 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training Tianlong Chen Zhenyu Zhang Pengju Wang Santosh Balachandra Haoyu Ma Zehao Wang Zhangyang Wang OOD AAML 100 47 0 20 Feb 2022
A Theory of PAC Learnability under Transformation Invariances Hang Shao Omar Montasser Avrim Blum 27 18 0 15 Feb 2022
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability Idan Attias Steve Hanneke Yishay Mansour 35 15 0 11 Feb 2022
Layer-wise Regularized Adversarial Training using Layers Sustainability Analysis (LSA) framework Mohammad Khalooei M. Homayounpour M. Amirmazlaghani AAML 25 3 0 05 Feb 2022
Can Adversarial Training Be Manipulated By Non-Robust Features? Lue Tao Lei Feng Hongxin Wei Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 139 16 0 31 Jan 2022
CommonsenseQA 2.0: Exposing the Limits of AI through Gamification Alon Talmor Ori Yoran Ronan Le Bras Chandrasekhar Bhagavatula Yoav Goldberg Yejin Choi Jonathan Berant ELM 33 141 0 14 Jan 2022
On Distinctive Properties of Universal Perturbations Sung Min Park K. Wei Kai Y. Xiao Jungshian Li A. Madry AAML 30 2 0 31 Dec 2021
Benign Overfitting in Adversarially Robust Linear Classification Jinghui Chen Yuan Cao Quanquan Gu AAML SILM 34 10 0 31 Dec 2021
On the Existence of the Adversarial Bayes Classifier (Extended Version) Pranjal Awasthi Natalie Frank M. Mohri 31 24 0 03 Dec 2021
Towards Understanding the Impact of Model Size on Differential Private Classification Yinchen Shen Zhiguo Wang Ruoyu Sun Xiaojing Shen 30 11 0 27 Nov 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps Muhammad Awais Fengwei Zhou Chuanlong Xie Jiawei Li Sung-Ho Bae Zhenguo Li AAML 43 17 0 09 Nov 2021
Towards Evaluating the Robustness of Neural Networks Learned by Transduction Jiefeng Chen Xi Wu Yang Guo Yingyu Liang S. Jha ELM AAML 23 15 0 27 Oct 2021
Transductive Robust Learning Guarantees Omar Montasser Steve Hanneke Nathan Srebro 26 13 0 20 Oct 2021
Improving Robustness using Generated Data Sven Gowal Sylvestre-Alvise Rebuffi Olivia Wiles Florian Stimberg D. A. Calian Timothy A. Mann 36 294 0 18 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 48 100 0 07 Oct 2021
Calibrated Adversarial Training Tianjin Huang Vlado Menkovski Yulong Pei Mykola Pechenizkiy AAML 64 3 0 01 Oct 2021
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective Adhyyan Narang Vidya Muthukumar A. Sahai SILM AAML 38 1 0 27 Sep 2021
Virtual Data Augmentation: A Robust and General Framework for Fine-tuning Pre-trained Models Kun Zhou Wayne Xin Zhao Sirui Wang Fuzheng Zhang Wei Wu Ji-Rong Wen AAML 34 7 0 13 Sep 2021
Regional Adversarial Training for Better Robust Generalization Chuanbiao Song Yanbo Fan Yichen Yang Baoyuan Wu Yiming Li Zhifeng Li Kun He AAML OOD 21 6 0 02 Sep 2021
Imbalanced Adversarial Training with Reweighting Wentao Wang Han Xu Xiaorui Liu Yaxin Li B. Thuraisingham Jiliang Tang 37 16 0 28 Jul 2021
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them Florian Tramèr AAML 30 65 0 24 Jul 2021
The Values Encoded in Machine Learning Research Abeba Birhane Pratyusha Kalluri Dallas Card William Agnew Ravit Dotan Michelle Bao 41 275 0 29 Jun 2021
Adversarial Training Helps Transfer Learning via Better Representations Zhun Deng Linjun Zhang Kailas Vodrahalli Kenji Kawaguchi James Zou GAN 36 54 0 18 Jun 2021
Adversarial Visual Robustness by Causal Intervention Kaihua Tang Ming Tao Hanwang Zhang CML AAML 32 21 0 17 Jun 2021
Pre-Trained Models: Past, Present and Future Xu Han Zhengyan Zhang Ning Ding Yuxian Gu Xiao Liu ... Jie Tang Ji-Rong Wen Jinhui Yuan Wayne Xin Zhao Jun Zhu AIFin MQ AI4MH 58 818 0 14 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 23 9 0 31 May 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 41 65 0 09 Apr 2021