v1v2v3 (latest)

Provable defenses against adversarial examples via the convex outer adversarial polytope

2 November 2017

Eric Wong

J. Zico Kolter

AAML

ArXiv (abs)PDF HTML Github (387★)

Papers citing "Provable defenses against adversarial examples via the convex outer adversarial polytope"

50 / 957 papers shown

Title
Deep Partition Aggregation: Provable Defense against General Poisoning Attacks Alexander Levine Soheil Feizi AAML 175 161 0 26 Jun 2020
The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network VerificationNeural Information Processing Systems (NeurIPS), 2020 Christian Tjandraatmadja Ross Anderson Joey Huchette Will Ma Krunal Patel J. Vielma AAML 185 96 0 24 Jun 2020
Bit Error Robustness for Energy-Efficient DNN Accelerators David Stutz Nandhini Chandramoorthy Matthias Hein Bernt Schiele MQ 241 1 0 24 Jun 2020
Learning to Generate Noise for Multi-Attack Robustness Divyam Madaan Jinwoo Shin Sung Ju Hwang NoLa AAML 398 29 0 22 Jun 2020
Sensitivity analysis of Wasserstein distributionally robust optimization problems Daniel Bartl Samuel Drapeau J. Obłój J. Wiesel 154 42 0 22 Jun 2020
Network Moments: Extensions and Sparse-Smooth Attacks Modar Alfadly Adel Bibi Emilio Botero Salman Alsubaihi Guohao Li AAML 109 2 0 21 Jun 2020
Verifying Individual Fairness in Machine Learning Models Philips George John Deepak Vijaykeerthy Diptikalyan Saha FaML 146 65 0 21 Jun 2020
A general framework for defining and optimizing robustness Alessandro Tibo M. Jaeger Kim G. Larsen 91 0 0 19 Jun 2020
PEREGRiNN: Penalized-Relaxation Greedy Neural Network Verifier Haitham Khedr James Ferlez Yasser Shoukry AAML 154 5 0 18 Jun 2020
On sparse connectivity, adversarial robustness, and a novel model of the artificial neuron Sergey Bochkanov AAML 182 1 0 16 Jun 2020
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and Faster Adversarial Robustness Proofs Christopher Brix T. Noll AAML 138 11 0 16 Jun 2020
Counterexample-Guided Learning of Monotonic Neural Networks Aishwarya Sivaraman G. Farnadi T. Millstein Karen Ullrich 137 61 0 16 Jun 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao Lin Ryota Tomioka Sabine Süsstrunk AAML 288 90 0 15 Jun 2020
Kernel Distributionally Robust Optimization Jia Jie Zhu Wittawat Jitkrittum Moritz Diehl Bernhard Schölkopf 378 16 0 12 Jun 2020
On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial ExamplesNeural Information Processing Systems (NeurIPS), 2020 Richard Y. Zhang AAML 229 27 0 11 Jun 2020
Provable tradeoffs in adversarially robust classification Guang Cheng Hamed Hassani David Hong Avi Schwarzschild 408 58 0 09 Jun 2020
Trade-offs between membership privacy & adversarially robust learning Jamie Hayes SILM 172 3 0 08 Jun 2020
Consistency Regularization for Certified Robustness of Smoothed Classifiers Jongheon Jeong Jinwoo Shin AAML 266 96 0 07 Jun 2020
Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing Vishaal Krishnan Abed AlRahman Al Makdah Fabio Pasqualetti OOD AAML 282 25 0 05 Jun 2020
Towards Understanding Fast Adversarial Training Bai Li Shiqi Wang Suman Jana Lawrence Carin AAML 110 51 0 04 Jun 2020
Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack Methods Kyungmi Lee A. Chandrakasan ELM AAML 114 3 0 01 Jun 2020
Second-Order Provable Defenses against Adversarial AttacksInternational Conference on Machine Learning (ICML), 2020 Sahil Singla Soheil Feizi AAML 161 62 0 01 Jun 2020
Evaluations and Methods for Explanation through Robustness AnalysisInternational Conference on Learning Representations (ICLR), 2019 Cheng-Yu Hsieh Chih-Kuan Yeh Xuanqing Liu Pradeep Ravikumar Seungyeon Kim Sanjiv Kumar Cho-Jui Hsieh XAI 162 68 0 31 May 2020
Adversarial Classification via Distributional Robustness with Wasserstein AmbiguityMathematical programming (Math. Program.), 2020 Nam Ho-Nguyen Stephen J. Wright OOD 306 20 0 28 May 2020
Calibrated Surrogate Losses for Adversarially Robust ClassificationAnnual Conference Computational Learning Theory (COLT), 2020 Han Bao Clayton Scott Masashi Sugiyama 216 47 0 28 May 2020
Arms Race in Adversarial Malware Detection: A Survey Deqiang Li Qianmu Li Yanfang Ye Shouhuai Xu AAML 254 55 0 24 May 2020
Model-Based Robust Deep Learning: Generalizing to Natural, Out-of-Distribution Data Avi Schwarzschild Hamed Hassani George J. Pappas OOD 256 42 0 20 May 2020
Enhancing Certified Robustness via Smoothed Weighted Ensembling Chizhou Liu Yunzhen Feng Ranran Wang Bin Dong AAML 194 12 0 19 May 2020
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking Chong Xiang A. Bhagoji Vikash Sehwag Prateek Mittal AAML 247 29 0 17 May 2020
Encryption Inspired Adversarial Defense for Visual Classification Maungmaung Aprilpyone Hitoshi Kiya 106 34 0 16 May 2020
Towards Assessment of Randomized Smoothing Mechanisms for Certifying Adversarial Robustness Tianhang Zheng Haiyan Zhao Baochun Li Jinhui Xu AAML 109 0 0 15 May 2020
Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition Tianhang Zheng Sheng Liu Changyou Chen Junsong Yuan Baochun Li K. Ren AAML 197 19 0 14 May 2020
Online Monitoring for Neural Network Based Monocular Pedestrian Pose Estimation Arjun Gupta Luca Carlone 3DH 147 9 0 11 May 2020
Efficient Exact Verification of Binarized Neural Networks Kai Jia Martin Rinard AAML MQ 151 66 0 07 May 2020
Lifted Regression/Reconstruction Networks R. Høier Christopher Zach 88 8 0 07 May 2020
Training robust neural networks using Lipschitz boundsIEEE Control Systems Letters (L-CSS), 2020 Patricia Pauli Anne Koch J. Berberich Paul Kohler Frank Allgöwer 270 194 0 06 May 2020
Measuring Adversarial Robustness using a Voronoi-Epsilon Adversary Hyeongji Kim P. Parviainen K. Malde 154 0 0 06 May 2020
Improved Image Wasserstein Attacks and Defenses J. E. Hu Adith Swaminathan Hadi Salman Greg Yang AAML OOD 170 11 0 26 Apr 2020
How to compare adversarial robustness of classifiers from a global perspective Niklas Risse Christina Göpfert Jan Philip Göpfert AAML 102 0 0 22 Apr 2020
Discovering Imperfectly Observable Adversarial Actions using Anomaly Detection Olga Petrova K. Durkota Galina Alperovich Karel Horak Michal Najman B. Bosanský Viliam Lisý AAML 69 1 0 22 Apr 2020
Provably robust deep generative models Filipe Condessa Zico Kolter AAML OOD 115 5 0 22 Apr 2020
Certifying Joint Adversarial Robustness for Model Ensembles M. Jonas David Evans AAML 128 2 0 21 Apr 2020
Single-step Adversarial training with Dropout SchedulingComputer Vision and Pattern Recognition (CVPR), 2020 S. VivekB. R. Venkatesh Babu OOD AAML 115 78 0 18 Apr 2020
Reach-SDP: Reachability Analysis of Closed-Loop Systems with Neural Network Controllers via Semidefinite ProgrammingIEEE Conference on Decision and Control (CDC), 2020 Haimin Hu Mahyar Fazlyab M. Morari George J. Pappas 138 84 0 16 Apr 2020
Adversarial Robustness Guarantees for Random Deep Neural NetworksInternational Conference on Machine Learning (ICML), 2020 Giacomo De Palma B. Kiani S. Lloyd AAML OOD 131 9 0 13 Apr 2020
Verification of Deep Convolutional Neural Networks Using ImageStarsInternational Conference on Computer Aided Verification (CAV), 2020 Hoang-Dung Tran Stanley Bak Weiming Xiang Taylor T. Johnson AAML 198 140 0 12 Apr 2020
Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement LearningIEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2020 Michael Everett Bjorn Lutjens Jonathan P. How AAML 352 50 0 11 Apr 2020
Understanding (Non-)Robust Feature Disentanglement and the Relationship Between Low- and High-Dimensional Adversarial Attacks Zuowen Wang Leo Horne AAML 107 0 0 04 Apr 2020
SOAR: Second-Order Adversarial Regularization A. Ma Fartash Faghri Nicolas Papernot Amir-massoud Farahmand AAML 122 4 0 04 Apr 2020
Tightened Convex Relaxations for Neural Network Robustness CertificationIEEE Conference on Decision and Control (CDC), 2020 Brendon G. Anderson Ziye Ma Jingqi Li Somayeh Sojoudi AAML 259 32 0 01 Apr 2020