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On Using Certified Training towards Empirical Robustness

2 October 2024

Papers citing "On Using Certified Training towards Empirical Robustness"

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Title
AdPO: Enhancing the Adversarial Robustness of Large Vision-Language Models with Preference Optimization Chaohu Liu Tianyi Gui Yu Liu Linli Xu VLM AAML 123 1 0 02 Apr 2025
CTBENCH: A Library and Benchmark for Certified Training Yuhao Mao Stefan Balauca Martin Vechev OOD 100 5 0 07 Jun 2024
Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency Runqi Lin Chaojian Yu Bo Han Hang Su Tongliang Liu AAML 117 4 0 25 May 2024
Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization Runqi Lin Chaojian Yu Tongliang Liu AAML 92 12 0 11 Apr 2024
Efficient local linearity regularization to overcome catastrophic overfitting Elias Abad Rocamora Fanghui Liu Grigorios G. Chrysos Pablo Martínez Olmos Volkan Cevher AAML 60 6 0 21 Jan 2024
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective Yifei Wang Liangchen Li Jiansheng Yang Zhouchen Lin Yisen Wang 66 15 0 30 Oct 2023
Understanding Certified Training with Interval Bound Propagation Yuhao Mao Mark Niklas Muller Marc Fischer Martin Vechev AAML 93 18 0 17 Jun 2023
How robust accuracy suffers from certified training with convex relaxations Piersilvio De Bartolomeis Jacob Clarysse Amartya Sanyal Fanny Yang AAML 61 2 0 12 Jun 2023
Expressive Losses for Verified Robustness via Convex Combinations Alessandro De Palma Rudy Bunel Krishnamurthy Dvijotham M. P. Kumar Robert Stanforth A. Lomuscio AAML 95 14 0 23 May 2023
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness Yuancheng Xu Yanchao Sun Micah Goldblum Tom Goldstein Furong Huang AAML 87 38 0 06 Feb 2023
$LOT: Layer-wise Orthogonal Training on Improving $\ell_2$ Certified Robustness$ LOT: Layer-wise Orthogonal Training on Improving $\ell_2$ Certified Robustness Xiaojun Xu Linyi Li Yue Liu OOD AAML 91 34 0 20 Oct 2022
Certified Training: Small Boxes are All You Need Mark Niklas Muller Franziska Eckert Marc Fischer Martin Vechev AAML 84 48 0 10 Oct 2022
Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective Bohang Zhang Du Jiang Di He Liwei Wang OOD 80 53 0 04 Oct 2022
General Cutting Planes for Bound-Propagation-Based Neural Network Verification Huan Zhang Shiqi Wang Kaidi Xu Linyi Li Yue Liu Suman Jana Cho-Jui Hsieh J. Zico Kolter 72 104 0 11 Aug 2022
IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound Alessandro De Palma Rudy Bunel Krishnamurthy Dvijotham M. P. Kumar Robert Stanforth AAML 68 17 0 29 Jun 2022
Catastrophic overfitting can be induced with discriminative non-robust features Guillermo Ortiz-Jiménez Pau de Jorge Amartya Sanyal Adel Bibi P. Dokania P. Frossard Grégory Rogez Philip Torr AAML 47 3 0 16 Jun 2022
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound Claudio Ferrari Mark Niklas Muller Nikola Jovanović Martin Vechev 79 91 0 30 Apr 2022
Make Some Noise: Reliable and Efficient Single-Step Adversarial Training Pau de Jorge Adel Bibi Riccardo Volpi Amartya Sanyal Philip Torr Grégory Rogez P. Dokania AAML 108 47 0 02 Feb 2022
Subspace Adversarial Training Tao Li Yingwen Wu Sizhe Chen Kun Fang Xiaolin Huang AAML OOD 104 59 0 24 Nov 2021
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds Yujia Huang Huan Zhang Yuanyuan Shi J Zico Kolter Anima Anandkumar 100 78 0 02 Nov 2021
Probabilistic Margins for Instance Reweighting in Adversarial Training Qizhou Wang Feng Liu Bo Han Tongliang Liu Chen Gong Gang Niu Mingyuan Zhou Masashi Sugiyama AAML 72 65 0 15 Jun 2021
Reliably fast adversarial training via latent adversarial perturbation Geon Yeong Park Sang Wan Lee AAML 65 28 0 04 Apr 2021
Fast Certified Robust Training with Short Warmup Zhouxing Shi Yihan Wang Huan Zhang Jinfeng Yi Cho-Jui Hsieh AAML 69 57 0 31 Mar 2021
On the Paradox of Certified Training Nikola Jovanović Mislav Balunović Maximilian Baader Martin Vechev OOD 90 13 0 12 Feb 2021
Fast Training of Provably Robust Neural Networks by SingleProp Akhilan Boopathy Tsui-Wei Weng Sijia Liu Pin-Yu Chen Gaoyuan Zhang Luca Daniel AAML 46 7 0 01 Feb 2021
Scaling the Convex Barrier with Sparse Dual Algorithms Alessandro De Palma Harkirat Singh Behl Rudy Bunel Philip Torr M. P. Kumar 101 9 0 14 Jan 2021
Understanding and Increasing Efficiency of Frank-Wolfe Adversarial Training Theodoros Tsiligkaridis Jay Roberts AAML 168 11 0 22 Dec 2020
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Gaurang Sriramanan Sravanti Addepalli Arya Baburaj R. Venkatesh Babu AAML 79 95 0 30 Nov 2020
Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers Kaidi Xu Huan Zhang Shiqi Wang Yihan Wang Suman Jana Xue Lin Cho-Jui Hsieh 113 188 0 27 Nov 2020
Understanding Catastrophic Overfitting in Single-step Adversarial Training Hoki Kim Woojin Lee Jaewook Lee AAML 120 112 0 05 Oct 2020
Adversarial Training and Provable Robustness: A Tale of Two Objectives Jiameng Fan Wenchao Li AAML 51 21 0 13 Aug 2020
Understanding and Improving Fast Adversarial Training Maksym Andriushchenko Nicolas Flammarion AAML 85 293 0 06 Jul 2020
The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification Christian Tjandraatmadja Ross Anderson Joey Huchette Will Ma Krunal Patel J. Vielma AAML 121 89 0 24 Jun 2020
Single-step Adversarial training with Dropout Scheduling S. VivekB. R. Venkatesh Babu OOD AAML 59 73 0 18 Apr 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 241 1,861 0 03 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 124 809 0 26 Feb 2020
Lagrangian Decomposition for Neural Network Verification Rudy Bunel Alessandro De Palma Alban Desmaison Krishnamurthy Dvijotham Pushmeet Kohli Philip Torr M. P. Kumar 75 50 0 24 Feb 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 142 1,181 0 12 Jan 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 568 42,677 0 03 Dec 2019
Square Attack: a query-efficient black-box adversarial attack via random search Maksym Andriushchenko Francesco Croce Nicolas Flammarion Matthias Hein AAML 103 992 0 29 Nov 2019
Towards Stable and Efficient Training of Verifiably Robust Neural Networks Huan Zhang Hongge Chen Chaowei Xiao Sven Gowal Robert Stanforth Yue Liu Duane S. Boning Cho-Jui Hsieh AAML 101 350 0 14 Jun 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 139 1,253 0 29 Apr 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 171 2,052 0 08 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 162 2,563 0 24 Jan 2019
Strong mixed-integer programming formulations for trained neural networks Ross Anderson Joey Huchette Christian Tjandraatmadja J. Vielma 176 258 0 20 Nov 2018
Efficient Neural Network Robustness Certification with General Activation Functions Huan Zhang Tsui-Wei Weng Pin-Yu Chen Cho-Jui Hsieh Luca Daniel AAML 101 765 0 02 Nov 2018
On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models Sven Gowal Krishnamurthy Dvijotham Robert Stanforth Rudy Bunel Chongli Qin J. Uesato Relja Arandjelović Timothy A. Mann Pushmeet Kohli AAML 100 559 0 30 Oct 2018
A Dual Approach to Scalable Verification of Deep Networks Krishnamurthy Dvijotham Dvijotham Robert Stanforth Sven Gowal Timothy A. Mann Pushmeet Kohli 61 399 0 17 Mar 2018
Provable defenses against adversarial examples via the convex outer adversarial polytope Eric Wong J. Zico Kolter AAML 138 1,504 0 02 Nov 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 163 2,160 0 21 Aug 2017