v1v2 (latest)

Certified Adversarial Robustness via Randomized Smoothing

8 February 2019

Jeremy M. Cohen

Elan Rosenfeld

J. Zico Kolter

AAML

ArXiv (abs)PDF HTML Github (390★)

Papers citing "Certified Adversarial Robustness via Randomized Smoothing"

50 / 1,313 papers shown

Title
Deep Learning Generalization and the Convex Hull of Training Sets Roozbeh Yousefzadeh 69 20 0 25 Jan 2021
Adversarial Machine Learning in Text Analysis and Generation I. Alsmadi AAML 114 5 0 14 Jan 2021
On the Effectiveness of Small Input Noise for Defending Against Query-based Black-Box Attacks Junyoung Byun Hyojun Go Changick Kim AAML 193 21 0 13 Jan 2021
Random Transformation of Image Brightness for Adversarial Attack Bo Yang Kaiyong Xu Hengjun Wang Hengwei Zhang AAML 52 8 0 12 Jan 2021
Towards a Robust and Trustworthy Machine Learning System Development: An Engineering Perspective Pulei Xiong Scott Buffett Shahrear Iqbal Philippe Lamontagne M. Mamun Heather Molyneaux OOD 92 15 0 08 Jan 2021
Adversarial Machine Learning for 5G Communications Security Y. Sagduyu T. Erpek Yi Shi AAML 85 43 0 07 Jan 2021
Adversarial Robustness by Design through Analog Computing and Synthetic Gradients Alessandro Cappelli Ruben Ohana Julien Launay Laurent Meunier Iacopo Poli Florent Krzakala AAML 131 13 0 06 Jan 2021
A Simple Fine-tuning Is All You Need: Towards Robust Deep Learning Via Adversarial Fine-tuning Ahmadreza Jeddi M. Shafiee A. Wong AAML 89 40 0 25 Dec 2020
Adversarial Momentum-Contrastive Pre-Training Cong Xu Dan Li Min Yang SSL 82 15 0 24 Dec 2020
Improving the Certified Robustness of Neural Networks via Consistency Regularization Mengting Xu Tao Zhang Zhongnian Li Daoqiang Zhang AAML 33 0 0 24 Dec 2020
Self-Progressing Robust Training Minhao Cheng Pin-Yu Chen Sijia Liu Shiyu Chang Cho-Jui Hsieh Payel Das AAML VLM 74 9 0 22 Dec 2020
Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead Maurizio Capra Beatrice Bussolino Alberto Marchisio Guido Masera Maurizio Martina Mohamed Bennai BDL 154 147 0 21 Dec 2020
Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification Shuyang Cheng Yingqi Liu Shiqing Ma Xinming Zhang AAML 122 160 0 21 Dec 2020
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses Micah Goldblum Dimitris Tsipras Chulin Xie Xinyun Chen Avi Schwarzschild Basel Alomair Aleksander Madry Yue Liu Tom Goldstein SILM 169 283 0 18 Dec 2020
RAILS: A Robust Adversarial Immune-inspired Learning System Ren Wang Tianqi Chen Stephen Lindsly A. Rehemtulla Alfred Hero I. Rajapakse AAML 54 7 0 18 Dec 2020
On the human-recognizability phenomenon of adversarially trained deep image classifiers Jonathan W. Helland Nathan M. VanHoudnos AAML 66 4 0 18 Dec 2020
Characterizing the Evasion Attackability of Multi-label Classifiers Zhuo Yang Yufei Han Xiangliang Zhang AAML 58 10 0 17 Dec 2020
TrojanZoo: Towards Unified, Holistic, and Practical Evaluation of Neural Backdoors Ren Pang Zheng Zhang Xiangshan Gao Zhaohan Xi S. Ji Peng Cheng Xiapu Luo Ting Wang AAML 100 32 0 16 Dec 2020
Adaptive Verifiable Training Using Pairwise Class Similarity Shiqi Wang Kevin Eykholt Taesung Lee Jiyong Jang Ian Molloy OOD 40 1 0 14 Dec 2020
Robustness Threats of Differential Privacy Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets AAML 100 14 0 14 Dec 2020
DSRNA: Differentiable Search of Robust Neural Architectures Ramtin Hosseini Xingyi Yang P. Xie OOD AAML 63 53 0 11 Dec 2020
Locally optimal detection of stochastic targeted universal adversarial perturbations Amish Goel P. Moulin AAML 67 2 0 08 Dec 2020
Data-Dependent Randomized Smoothing Motasem Alfarra Adel Bibi Philip Torr Guohao Li UQCV 125 35 0 08 Dec 2020
A Singular Value Perspective on Model Robustness Malhar Jere Maghav Kumar F. Koushanfar AAML 86 6 0 07 Dec 2020
Learning to Separate Clusters of Adversarial Representations for Robust Adversarial Detection Byunggill Joe Jihun Hamm Sung Ju Hwang Sooel Son I. Shin AAML OOD 72 0 0 07 Dec 2020
Advocating for Multiple Defense Strategies against Adversarial Examples Alexandre Araujo Laurent Meunier Rafael Pinot Benjamin Négrevergne AAML 53 9 0 04 Dec 2020
Interpretable Graph Capsule Networks for Object Recognition Jindong Gu Volker Tresp FAtt 76 36 0 03 Dec 2020
From a Fourier-Domain Perspective on Adversarial Examples to a Wiener Filter Defense for Semantic Segmentation Nikhil Kapoor Andreas Bär Serin Varghese Jan David Schneider Fabian Hüger Peter Schlicht Tim Fingscheidt AAML 76 10 0 02 Dec 2020
How Robust are Randomized Smoothing based Defenses to Data Poisoning? Akshay Mehra B. Kailkhura Pin-Yu Chen Jihun Hamm OOD AAML 130 32 0 02 Dec 2020
Adversarial Robustness Across Representation Spaces Pranjal Awasthi George Yu Chun-Sung Ferng Andrew Tomkins Da-Cheng Juan OOD AAML 91 11 0 01 Dec 2020
Boosting Adversarial Attacks on Neural Networks with Better Optimizer Heng Yin Hengwei Zhang Jin-dong Wang Ruiyu Dou AAML 91 8 0 01 Dec 2020
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Gaurang Sriramanan Sravanti Addepalli Arya Baburaj R. Venkatesh Babu AAML 95 95 0 30 Nov 2020
Deterministic Certification to Adversarial Attacks via Bernstein Polynomial Approximation Ching-Chia Kao Jhe-Bang Ko Chun-Shien Lu AAML 68 1 0 28 Nov 2020
Better Aggregation in Test-Time Augmentation Divya Shanmugam Davis W. Blalock Guha Balakrishnan John Guttag ViT 107 148 0 23 Nov 2020
A Neuro-Inspired Autoencoding Defense Against Adversarial Perturbations Can Bakiskan Metehan Cekic Ahmet Dundar Sezer Upamanyu Madhow AAML 54 0 0 21 Nov 2020
Adversarial Examples for $k$ -Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams Chawin Sitawarin Evgenios M. Kornaropoulos Basel Alomair David Wagner AAML 52 8 0 19 Nov 2020
Shaping Deep Feature Space towards Gaussian Mixture for Visual Classification Weitao Wan Jiansheng Chen Cheng Yu Tong Wu Yuanyi Zhong Ming-Hsuan Yang 53 8 0 18 Nov 2020
Extreme Value Preserving Networks Mingjie Sun Jianguo Li Changshui Zhang AAML MDE 37 0 0 17 Nov 2020
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations Jinyuan Jia Binghui Wang Xiaoyu Cao Hongbin Liu Neil Zhenqiang Gong 88 24 0 15 Nov 2020
Towards transformation-resilient provenance detection of digital media Jamie Hayes Krishnamurthy Dvijotham Dvijotham Yutian Chen Sander Dieleman Pushmeet Kohli Norman Casagrande 40 3 0 14 Nov 2020
A survey on practical adversarial examples for malware classifiers Daniel Park B. Yener AAML 100 16 0 06 Nov 2020
Defense-friendly Images in Adversarial Attacks: Dataset and Metrics for Perturbation Difficulty Camilo Pestana Wei Liu D. Glance Ajmal Mian AAML 155 5 0 05 Nov 2020
Trustworthy AI Richa Singh Mayank Vatsa Nalini Ratha 68 4 0 02 Nov 2020
Reliable Graph Neural Networks via Robust Aggregation Simon Geisler Daniel Zügner Stephan Günnemann AAML OOD 60 72 0 29 Oct 2020
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? Anna-Kathrin Kopetzki Bertrand Charpentier Daniel Zügner Sandhya Giri Stephan Günnemann 91 48 0 28 Oct 2020
Attack Agnostic Adversarial Defense via Visual Imperceptible Bound S. Chhabra Akshay Agarwal Richa Singh Mayank Vatsa AAML 69 3 0 25 Oct 2020
Adversarial Robustness of Supervised Sparse Coding Jeremias Sulam Ramchandran Muthumukar R. Arora AAML 72 23 0 22 Oct 2020
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming Sumanth Dathathri Krishnamurthy Dvijotham Alexey Kurakin Aditi Raghunathan J. Uesato ... Shreya Shankar Jacob Steinhardt Ian Goodfellow Percy Liang Pushmeet Kohli AAML 120 95 0 22 Oct 2020
Certified Distributional Robustness on Smoothed Classifiers Jungang Yang Liyao Xiang Pengzhi Chu Yukun Wang Cheng Zhou Xinbing Wang AAML 65 0 0 21 Oct 2020
Tight Second-Order Certificates for Randomized Smoothing Alexander Levine Aounon Kumar Thomas A. Goldstein Soheil Feizi AAML 63 16 0 20 Oct 2020