A Kernel Perspective for Regularizing Deep Neural Networks

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A Kernel Perspective for Regularizing Deep Neural Networks

30 September 2018

Grégoire Mialon

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Papers citing "A Kernel Perspective for Regularizing Deep Neural Networks"

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Title
Jacobian Norm with Selective Input Gradient Regularization for Improved and Interpretable Adversarial Defense Deyin Liu Lin Wu Haifeng Zhao F. Boussaïd Bennamoun Xianghua Xie AAML 260 3 0 09 Jul 2022
A Fast and Efficient Conditional Learning for Tunable Trade-Off between Accuracy and Robustness Souvik Kundu Sairam Sundaresan Massoud Pedram Peter A. Beerel AAML 128 1 0 28 Mar 2022
Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution Yunshi Huang Émilie Chouzenoux J. Pesquet BDL 163 13 0 14 Oct 2021
On Robustness to Adversarial Examples and Polynomial OptimizationNeural Information Processing Systems (NeurIPS), 2019 Pranjal Awasthi Abhratanu Dutta Aravindan Vijayaraghavan OOD AAML 156 34 0 12 Nov 2019
Adversarial Training is a Form of Data-dependent Operator Norm Regularization Kevin Roth Yannic Kilcher Thomas Hofmann 186 13 0 04 Jun 2019
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial AttackComputer Vision and Pattern Recognition (CVPR), 2018 Adnan Siraj Rakin Zhezhi He Deliang Fan AAML 143 307 0 22 Nov 2018