Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks

12 February 2018

Papers citing "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks"

50 / 57 papers shown

Title
Hadamard product in deep learning: Introduction, Advances and Challenges Grigorios G. Chrysos Yongtao Wu Razvan Pascanu Philip Torr V. Cevher AAML 98 0 0 17 Apr 2025
Bridging the Theoretical Gap in Randomized Smoothing Blaise Delattre Paul Caillon Quentin Barthélemy Erwan Fagnou Alexandre Allauzen AAML 50 0 0 03 Apr 2025
Improved Scalable Lipschitz Bounds for Deep Neural Networks U. Syed Bin Hu BDL 56 0 0 18 Mar 2025
On Space Folds of ReLU Neural Networks Michal Lewandowski Hamid Eghbalzadeh Bernhard Heinzl Raphael Pisoni Bernhard A.Moser MLT 73 1 0 17 Feb 2025
SPLITZ: Certifiable Robustness via Split Lipschitz Randomized Smoothing Meiyu Zhong Ravi Tandon 36 3 0 03 Jul 2024
Compositional Curvature Bounds for Deep Neural Networks Taha Entesari Sina Sharifi Mahyar Fazlyab AAML 34 0 0 07 Jun 2024
The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective Nils Philipp Walter Linara Adilova Jilles Vreeken Michael Kamp AAML 43 2 0 27 May 2024
Careful with that Scalpel: Improving Gradient Surgery with an EMA Yu-Guan Hsieh James Thornton Eugène Ndiaye Michal Klein Marco Cuturi Pierre Ablin MedIm 31 0 0 05 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 19 5 0 02 Feb 2024
How Smooth Is Attention? Valérie Castin Pierre Ablin Gabriel Peyré AAML 40 9 0 22 Dec 2023
1-Lipschitz Neural Networks are more expressive with N-Activations Bernd Prach Christoph H. Lampert AAML FAtt 24 0 0 10 Nov 2023
LipSim: A Provably Robust Perceptual Similarity Metric Sara Ghazanfari Alexandre Araujo P. Krishnamurthy Farshad Khorrami Siddharth Garg 26 5 0 27 Oct 2023
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization Mahyar Fazlyab Taha Entesari Aniket Roy Ramalingam Chellappa AAML 13 11 0 29 Sep 2023
Robust low-rank training via approximate orthonormal constraints Dayana Savostianova Emanuele Zangrando Gianluca Ceruti Francesco Tudisco 21 9 0 02 Jun 2023
Steerable Equivariant Representation Learning Sangnie Bhardwaj Willie McClinton Tongzhou Wang Guillaume Lajoie Chen Sun Phillip Isola Dilip Krishnan OOD LLMSV 26 5 0 22 Feb 2023
CQnet: convex-geometric interpretation and constraining neural-network trajectories B. Peters 24 0 0 09 Feb 2023
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion Zhuoqun Huang Neil G. Marchant Keane Lucas Lujo Bauer O. Ohrimenko Benjamin I. P. Rubinstein AAML 22 14 0 31 Jan 2023
Orthogonal SVD Covariance Conditioning and Latent Disentanglement Yue Song N. Sebe Wei Wang 23 6 0 11 Dec 2022
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack Yunfeng Diao He-Nan Wang Tianjia Shao Yong-Liang Yang Kun Zhou David C. Hogg Meng Wang AAML 32 6 0 21 Nov 2022
Improved techniques for deterministic l2 robustness Sahil Singla S. Feizi AAML 23 9 0 15 Nov 2022
Dynamical systems' based neural networks E. Celledoni Davide Murari B. Owren Carola-Bibiane Schönlieb Ferdia Sherry OOD 38 10 0 05 Oct 2022
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks Bernd Prach Christoph H. Lampert 30 35 0 05 Aug 2022
Improving Covariance Conditioning of the SVD Meta-layer by Orthogonality Yue Song N. Sebe Wei Wang 10 8 0 05 Jul 2022
On the Role of Generalization in Transferability of Adversarial Examples Yilin Wang Farzan Farnia AAML 24 10 0 18 Jun 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 16 48 0 01 May 2022
Approximation of Lipschitz Functions using Deep Spline Neural Networks Sebastian Neumayer Alexis Goujon Pakshal Bohra M. Unser 19 15 0 13 Apr 2022
Toward Robust Spiking Neural Network Against Adversarial Perturbation Ling Liang Kaidi Xu Xing Hu Lei Deng Yuan Xie AAML 29 13 0 12 Apr 2022
Defending Black-box Skeleton-based Human Activity Classifiers He-Nan Wang Yunfeng Diao Zichang Tan G. Guo AAML 45 10 0 09 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 32 13 0 26 Feb 2022
Is the Rush to Machine Learning Jeopardizing Safety? Results of a Survey M. Askarpour Alan Wassyng M. Lawford R. Paige Z. Diskin 15 0 0 29 Nov 2021
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds Yujia Huang Huan Zhang Yuanyuan Shi J Zico Kolter Anima Anandkumar 27 76 0 02 Nov 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 44 100 0 07 Oct 2021
Orthogonal Graph Neural Networks Kai Guo Kaixiong Zhou Xia Hu Yu Li Yi Chang Xin Wang 41 34 0 23 Sep 2021
Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks E. M. Achour Franccois Malgouyres Franck Mamalet 16 20 0 12 Aug 2021
Certification of embedded systems based on Machine Learning: A survey Guillaume Vidot Christophe Gabreau I. Ober Iulian Ober 6 12 0 14 Jun 2021
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective Florin Gogianu Tudor Berariu Mihaela Rosca Claudia Clopath L. Buşoniu Razvan Pascanu 16 52 0 11 May 2021
Analytical bounds on the local Lipschitz constants of ReLU networks Trevor Avant K. Morgansen FAtt 14 12 0 29 Apr 2021
A case for new neural network smoothness constraints Mihaela Rosca T. Weber A. Gretton S. Mohamed AAML 25 48 0 14 Dec 2020
Geometry-aware Instance-reweighted Adversarial Training Jingfeng Zhang Jianing Zhu Gang Niu Bo Han Masashi Sugiyama Mohan S. Kankanhalli AAML 16 269 0 05 Oct 2020
The Lipschitz Constant of Self-Attention Hyunjik Kim George Papamakarios A. Mnih 8 134 0 08 Jun 2020
Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao Clayton Scott Masashi Sugiyama 8 45 0 28 May 2020
Training robust neural networks using Lipschitz bounds Patricia Pauli Anne Koch J. Berberich Paul Kohler Frank Allgöwer 14 156 0 06 May 2020
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger Jingfeng Zhang Xilie Xu Bo Han Gang Niu Li-zhen Cui Masashi Sugiyama Mohan S. Kankanhalli AAML 14 396 0 26 Feb 2020
Indirect Adversarial Attacks via Poisoning Neighbors for Graph Convolutional Networks Tsubasa Takahashi GNN AAML 6 37 0 19 Feb 2020
Semialgebraic Optimization for Lipschitz Constants of ReLU Networks Tong Chen J. Lasserre Victor Magron Edouard Pauwels 17 3 0 10 Feb 2020
Softmax-based Classification is k-means Clustering: Formal Proof, Consequences for Adversarial Attacks, and Improvement through Centroid Based Tailoring Sibylle Hess W. Duivesteijn D. Mocanu 12 12 0 07 Jan 2020
Fine-grained Synthesis of Unrestricted Adversarial Examples Omid Poursaeed Tianxing Jiang Yordanos Goshu Harry Yang Serge J. Belongie Ser-Nam Lim AAML 30 13 0 20 Nov 2019
Where is the Bottleneck of Adversarial Learning with Unlabeled Data? Jingfeng Zhang Bo Han Gang Niu Tongliang Liu Masashi Sugiyama 8 6 0 20 Nov 2019
A Frobenius norm regularization method for convolutional kernels to avoid unstable gradient problem Pei-Chang Guo 13 5 0 25 Jul 2019
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 8 77 0 27 May 2019