Provable Robustness of ReLU networks via Maximization of Linear Regions

17 October 2018

Matthias Hein

Papers citing "Provable Robustness of ReLU networks via Maximization of Linear Regions"

31 / 31 papers shown

Title
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 94 32 0 29 Apr 2023
Confidence-aware Training of Smoothed Classifiers for Certified Robustness Jongheon Jeong Seojin Kim Jinwoo Shin AAML 19 7 0 18 Dec 2022
Towards Robust Dataset Learning Yihan Wu Xinda Li Florian Kerschbaum Heng Huang Hongyang R. Zhang DD OOD 41 10 0 19 Nov 2022
Improved techniques for deterministic l2 robustness Sahil Singla S. Feizi AAML 23 9 0 15 Nov 2022
Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu Ziqi Zhao Sabine Süsstrunk Mathieu Salzmann TPM AAML MQ 19 4 0 03 Feb 2022
The Fundamental Limits of Interval Arithmetic for Neural Networks M. Mirman Maximilian Baader Martin Vechev 17 6 0 09 Dec 2021
Adversarial Robustness via Fisher-Rao Regularization Marine Picot Francisco Messina Malik Boudiaf Fabrice Labeau Ismail Ben Ayed Pablo Piantanida AAML 20 23 0 12 Jun 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 27 65 0 09 Apr 2021
On the Adversarial Robustness of Vision Transformers Rulin Shao Zhouxing Shi Jinfeng Yi Pin-Yu Chen Cho-Jui Hsieh ViT 30 137 0 29 Mar 2021
Robust Models Are More Interpretable Because Attributions Look Normal Zifan Wang Matt Fredrikson Anupam Datta OOD FAtt 28 25 0 20 Mar 2021
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack Mengting Xu Tao Zhang Zhongnian Li Mingxia Liu Daoqiang Zhang AAML OOD MedIm 25 41 0 05 Mar 2021
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients Yifei Huang Yaodong Yu Hongyang R. Zhang Yi-An Ma Yuan Yao AAML 29 26 0 28 Sep 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 19 81 0 15 Jun 2020
ReLU Code Space: A Basis for Rating Network Quality Besides Accuracy Natalia Shepeleva Werner Zellinger Michal Lewandowski Bernhard A. Moser 17 3 0 20 May 2020
Topological Effects on Attacks Against Vertex Classification B. A. Miller Mustafa Çamurcu Alexander J. Gomez Kevin S. Chan Tina Eliassi-Rad AAML 9 2 0 12 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 30 785 0 26 Feb 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 46 1,158 0 12 Jan 2020
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 26 68 0 06 Nov 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 24 91 0 29 Sep 2019
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks Alejandro Molina P. Schramowski Kristian Kersting ODL 16 77 0 15 Jul 2019
Certifiable Robustness and Robust Training for Graph Convolutional Networks Daniel Zügner Stephan Günnemann OffRL 31 159 0 28 Jun 2019
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers Hadi Salman Greg Yang Jungshian Li Pengchuan Zhang Huan Zhang Ilya P. Razenshteyn Sébastien Bubeck AAML 25 535 0 09 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 20 61 0 08 Jun 2019
Robustness for Non-Parametric Classification: A Generic Attack and Defense Yao-Yuan Yang Cyrus Rashtchian Yizhen Wang Kamalika Chaudhuri SILM AAML 29 42 0 07 Jun 2019
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks Francesco Croce Jonas Rauber Matthias Hein AAML 20 30 0 27 Mar 2019
MMA Training: Direct Input Space Margin Maximization through Adversarial Training G. Ding Yash Sharma Kry Yik-Chau Lui Ruitong Huang AAML 16 270 0 06 Dec 2018
Prototype-based Neural Network Layers: Incorporating Vector Quantization S. Saralajew Lars Holdijk Maike Rees T. Villmann MQ 17 15 0 04 Dec 2018
Logit Pairing Methods Can Fool Gradient-Based Attacks Marius Mosbach Maksym Andriushchenko T. A. Trost Matthias Hein Dietrich Klakow AAML 19 82 0 29 Oct 2018
Empirical Bounds on Linear Regions of Deep Rectifier Networks Thiago Serra Srikumar Ramalingam 8 42 0 08 Oct 2018
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 228 1,835 0 03 Feb 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 284 5,835 0 08 Jul 2016