Robustness May Be at Odds with Accuracy

30 May 2018

Papers citing "Robustness May Be at Odds with Accuracy"

50 / 433 papers shown

Title
On the Limitations of Stochastic Pre-processing Defenses Yue Gao Ilia Shumailov Kassem Fawaz Nicolas Papernot AAML SILM 47 31 0 19 Jun 2022
The Consistency of Adversarial Training for Binary Classification Natalie Frank Jonathan Niles-Weed AAML 43 5 0 18 Jun 2022
Analysis and Extensions of Adversarial Training for Video Classification K. A. Kinfu René Vidal AAML 33 13 0 16 Jun 2022
Reconstructing Training Data from Trained Neural Networks Niv Haim Gal Vardi Gilad Yehudai Ohad Shamir Michal Irani 42 132 0 15 Jun 2022
Multi-Objective Hyperparameter Optimization in Machine Learning -- An Overview Florian Karl Tobias Pielok Julia Moosbauer Florian Pfisterer Stefan Coors ... Jakob Richter Michel Lang Eduardo C. Garrido-Merchán Juergen Branke B. Bischl AI4CE 26 57 0 15 Jun 2022
Exploring Adversarial Attacks and Defenses in Vision Transformers trained with DINO Javier Rando Nasib Naimi Thomas Baumann Max Mathys AAML 20 5 0 14 Jun 2022
Wavelet Regularization Benefits Adversarial Training Jun Yan Huilin Yin Xiaoyang Deng Zi-qin Zhao Wancheng Ge Hao Zhang Gerhard Rigoll AAML 24 2 0 08 Jun 2022
Analyzing Modality Robustness in Multimodal Sentiment Analysis Devamanyu Hazarika Yingting Li Bo Cheng Shuai Zhao Roger Zimmermann Soujanya Poria 48 32 0 30 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 84 27 0 27 May 2022
B-cos Networks: Alignment is All We Need for Interpretability Moritz D Boehle Mario Fritz Bernt Schiele 48 85 0 20 May 2022
Sparse Visual Counterfactual Explanations in Image Space Valentyn Boreiko Maximilian Augustin Francesco Croce Philipp Berens Matthias Hein BDL CML 32 26 0 16 May 2022
Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell AAML 21 5 0 12 May 2022
How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations? Alvin Chan Yew-Soon Ong Clement Tan AAML 24 13 0 09 May 2022
SSR-GNNs: Stroke-based Sketch Representation with Graph Neural Networks Sheng Cheng Yi Ren Yezhou Yang 56 2 0 27 Apr 2022
On Fragile Features and Batch Normalization in Adversarial Training Nils Philipp Walter David Stutz Bernt Schiele AAML 27 5 0 26 Apr 2022
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning Mathias Lechner Alexander Amini Daniela Rus T. Henzinger AAML 34 10 0 15 Apr 2022
A Simple Approach to Adversarial Robustness in Few-shot Image Classification Akshayvarun Subramanya Hamed Pirsiavash VLM 29 6 0 11 Apr 2022
Anti-Adversarially Manipulated Attributions for Weakly Supervised Semantic Segmentation and Object Localization Jungbeom Lee Eunji Kim J. Mok Sung-Hoon Yoon WSOL 42 29 0 11 Apr 2022
Does Robustness on ImageNet Transfer to Downstream Tasks? Yutaro Yamada Mayu Otani OOD 32 27 0 08 Apr 2022
The Effects of Regularization and Data Augmentation are Class Dependent Randall Balestriero Léon Bottou Yann LeCun 41 94 0 07 Apr 2022
Training-Free Robust Multimodal Learning via Sample-Wise Jacobian Regularization Zhengqi Gao Sucheng Ren Zihui Xue Siting Li Hang Zhao 24 3 0 05 Apr 2022
Robust and Accurate -- Compositional Architectures for Randomized Smoothing Miklós Z. Horváth Mark Niklas Muller Marc Fischer Martin Vechev UQCV AAML 10 13 0 01 Apr 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective Yimeng Zhang Yuguang Yao Jinghan Jia Jinfeng Yi Min-Fong Hong Shiyu Chang Sijia Liu AAML 26 33 0 27 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
A Manifold View of Adversarial Risk Wen-jun Zhang Yikai Zhang Xiaoling Hu Mayank Goswami Chao Chen Dimitris N. Metaxas AAML 19 6 0 24 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
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization Junyuan Hong Haotao Wang Zhangyang Wang Jiayu Zhou FedML 27 56 0 18 Mar 2022
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse Martin Pawelczyk Teresa Datta Johannes van-den-Heuvel Gjergji Kasneci Himabindu Lakkaraju 24 38 0 13 Mar 2022
Defending Black-box Skeleton-based Human Activity Classifiers He Wang Yunfeng Diao Zichang Tan G. Guo AAML 53 10 0 09 Mar 2022
Why adversarial training can hurt robust accuracy Jacob Clarysse Julia Hörrmann Fanny Yang AAML 15 18 0 03 Mar 2022
Limitations of Deep Learning for Inverse Problems on Digital Hardware Holger Boche Adalbert Fono Gitta Kutyniok 32 25 0 28 Feb 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 34 13 0 26 Feb 2022
On the Effectiveness of Adversarial Training against Backdoor Attacks Yinghua Gao Dongxian Wu Jingfeng Zhang Guanhao Gan Shutao Xia Gang Niu Masashi Sugiyama AAML 32 22 0 22 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang Min Lin Xiao Yang Junyi Zhu Shuicheng Yan 37 120 0 21 Feb 2022
Exploring Adversarially Robust Training for Unsupervised Domain Adaptation Shao-Yuan Lo Vishal M. Patel AAML 39 8 0 18 Feb 2022
Verification-Aided Deep Ensemble Selection Guy Amir Tom Zelazny Guy Katz Michael Schapira AAML 30 18 0 08 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
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks A. Harrington Arturo Deza OOD AAML 29 20 0 02 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
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations Amin Ghiasi Hamid Kazemi Steven Reich Chen Zhu Micah Goldblum Tom Goldstein 48 15 0 31 Jan 2022
Efficient and Robust Classification for Sparse Attacks M. Beliaev Payam Delgosha Hamed Hassani Ramtin Pedarsani AAML 27 2 0 23 Jan 2022
On Distinctive Properties of Universal Perturbations Sung Min Park K. Wei Kai Y. Xiao Jungshian Li A. Madry AAML 24 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
Closer Look at the Transferability of Adversarial Examples: How They Fool Different Models Differently Futa Waseda Sosuke Nishikawa Trung-Nghia Le H. Nguyen Isao Echizen SILM 36 35 0 29 Dec 2021
How Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness? Xinhsuai Dong Anh Tuan Luu Min Lin Shuicheng Yan Hanwang Zhang SILM AAML 22 55 0 22 Dec 2021
Improving Robustness with Image Filtering M. Terzi Mattia Carletti Gian Antonio Susto AAML 29 0 0 21 Dec 2021
All You Need is RAW: Defending Against Adversarial Attacks with Camera Image Pipelines Yuxuan Zhang B. Dong Felix Heide AAML 26 8 0 16 Dec 2021
Measure and Improve Robustness in NLP Models: A Survey Xuezhi Wang Haohan Wang Diyi Yang 139 131 0 15 Dec 2021
The King is Naked: on the Notion of Robustness for Natural Language Processing Emanuele La Malfa Marta Z. Kwiatkowska 20 28 0 13 Dec 2021
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses Chun Pong Lau Jiang-Long Liu Hossein Souri Wei-An Lin S. Feizi Ramalingam Chellappa AAML 31 12 0 12 Dec 2021