Provable defenses against adversarial examples via the convex outer adversarial polytope

2 November 2017

J. Zico Kolter

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

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Title
The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results Stanley Bak Changliu Liu Taylor T. Johnson NAI 25 112 0 31 Aug 2021
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier Chong Xiang Saeed Mahloujifar Prateek Mittal VLM AAML 24 73 0 20 Aug 2021
Neural Architecture Dilation for Adversarial Robustness Yanxi Li Zhaohui Yang Yunhe Wang Chang Xu AAML 38 23 0 16 Aug 2021
Reachability Analysis of Neural Feedback Loops M. Everett Golnaz Habibi Chuangchuang Sun Jonathan P. How 19 53 0 09 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 31 236 0 01 Aug 2021
Neural Network Branch-and-Bound for Neural Network Verification Florian Jaeckle Jingyue Lu M. P. Kumar 18 8 0 27 Jul 2021
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them Florian Tramèr AAML 30 65 0 24 Jul 2021
On the Certified Robustness for Ensemble Models and Beyond Zhuolin Yang Linyi Li Xiaojun Xu B. Kailkhura Tao Xie Bo-wen Li AAML 29 48 0 22 Jul 2021
Built-in Elastic Transformations for Improved Robustness Sadaf Gulshad Ivan Sosnovik A. Smeulders AAML 22 1 0 20 Jul 2021
GoTube: Scalable Stochastic Verification of Continuous-Depth Models Sophie Gruenbacher Mathias Lechner Ramin Hasani Daniela Rus T. Henzinger S. Smolka Radu Grosu 26 17 0 18 Jul 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 104 196 0 12 Jul 2021
Provable Lipschitz Certification for Generative Models Matt Jordan A. Dimakis 22 14 0 06 Jul 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 24 4 0 06 Jul 2021
Scalable Certified Segmentation via Randomized Smoothing Marc Fischer Maximilian Baader Martin Vechev 18 38 0 01 Jul 2021
Certified Robustness via Randomized Smoothing over Multiplicative Parameters of Input Transformations Nikita Muravev Aleksandr Petiushko AAML 18 7 0 28 Jun 2021
Policy Smoothing for Provably Robust Reinforcement Learning Aounon Kumar Alexander Levine S. Feizi AAML 20 56 0 21 Jun 2021
Adversarial Visual Robustness by Causal Intervention Kaihua Tang Ming Tao Hanwang Zhang CML AAML 27 21 0 17 Jun 2021
Localized Uncertainty Attacks Ousmane Amadou Dia Theofanis Karaletsos C. Hazirbas Cristian Canton Ferrer I. Kabul E. Meijer AAML 24 2 0 17 Jun 2021
DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting Shaoru Chen Eric Wong Zico Kolter Mahyar Fazlyab 47 15 0 16 Jun 2021
Adversarial Robustness via Fisher-Rao Regularization Marine Picot Francisco Messina Malik Boudiaf Fabrice Labeau Ismail Ben Ayed Pablo Piantanida AAML 28 23 0 12 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 21 31 0 09 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 23 9 0 31 May 2021
DNNV: A Framework for Deep Neural Network Verification David Shriver Sebastian G. Elbaum Matthew B. Dwyer 21 31 0 26 May 2021
Practical Convex Formulation of Robust One-hidden-layer Neural Network Training Yatong Bai Tanmay Gautam Yujie Gai Somayeh Sojoudi AAML 27 3 0 25 May 2021
Decentralized Inference with Graph Neural Networks in Wireless Communication Systems Mengyuan Lee Guanding Yu H. Dai GNN 42 40 0 19 Apr 2021
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators David Stutz Nandhini Chandramoorthy Matthias Hein Bernt Schiele AAML MQ 24 18 0 16 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 36 65 0 09 Apr 2021
A Review of Formal Methods applied to Machine Learning Caterina Urban Antoine Miné 39 55 0 06 Apr 2021
Robust Models Are More Interpretable Because Attributions Look Normal Zifan Wang Matt Fredrikson Anupam Datta OOD FAtt 35 25 0 20 Mar 2021
Adversarial Training is Not Ready for Robot Learning Mathias Lechner Ramin Hasani Radu Grosu Daniela Rus T. Henzinger AAML 38 34 0 15 Mar 2021
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness Jacob D. Abernethy Pranjal Awasthi Satyen Kale AAML 27 6 0 01 Mar 2021
Towards Robust and Reliable Algorithmic Recourse Sohini Upadhyay Shalmali Joshi Himabindu Lakkaraju 25 108 0 26 Feb 2021
Adversarial Robustness with Non-uniform Perturbations Ece Naz Erdemir Jeffrey Bickford Luca Melis Sergul Aydore AAML 24 26 0 24 Feb 2021
Model-Based Domain Generalization Alexander Robey George J. Pappas Hamed Hassani OOD 45 129 0 23 Feb 2021
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning Ren Wang Kaidi Xu Sijia Liu Pin-Yu Chen Tsui-Wei Weng Chuang Gan Meng Wang AAML 21 47 0 20 Feb 2021
Adversarially Robust Kernel Smoothing Jia-Jie Zhu Christina Kouridi Yassine Nemmour Bernhard Schölkopf 28 7 0 16 Feb 2021
Globally-Robust Neural Networks Klas Leino Zifan Wang Matt Fredrikson AAML OOD 80 126 0 16 Feb 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs S. Feizi AAML 32 45 0 15 Feb 2021
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS Felix O. Olowononi D. Rawat Chunmei Liu 36 133 0 14 Feb 2021
On the Paradox of Certified Training Nikola Jovanović Mislav Balunović Maximilian Baader Martin Vechev OOD 28 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 11 7 0 01 Feb 2021
Increasing the Confidence of Deep Neural Networks by Coverage Analysis Giulio Rossolini Alessandro Biondi Giorgio Buttazzo AAML 26 13 0 28 Jan 2021
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification Brendon G. Anderson Ziye Ma Jingqi Li Somayeh Sojoudi 58 1 0 22 Jan 2021
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary Huan Zhang Hongge Chen Duane S. Boning Cho-Jui Hsieh 67 163 0 21 Jan 2021
Fundamental Tradeoffs in Distributionally Adversarial Training M. Mehrabi Adel Javanmard Ryan A. Rossi Anup B. Rao Tung Mai AAML 20 18 0 15 Jan 2021
Achieving Adversarial Robustness Requires An Active Teacher Chao Ma Lexing Ying 27 1 0 14 Dec 2020
DSRNA: Differentiable Search of Robust Neural Architectures Ramtin Hosseini Xingyi Yang P. Xie OOD AAML 29 50 0 11 Dec 2020
Data-Dependent Randomized Smoothing Motasem Alfarra Adel Bibi Philip Torr Guohao Li UQCV 28 34 0 08 Dec 2020
Interpretable Graph Capsule Networks for Object Recognition Jindong Gu Volker Tresp FAtt 19 36 0 03 Dec 2020
A Study on the Uncertainty of Convolutional Layers in Deep Neural Networks Hao Shen Sihong Chen Ran Wang 30 5 0 27 Nov 2020