Spectral Norm Regularization for Improving the Generalizability of Deep Learning

31 May 2017

Papers citing "Spectral Norm Regularization for Improving the Generalizability of Deep Learning"

22 / 72 papers shown

Title
Stable and expressive recurrent vision models Drew Linsley A. Ashok L. Govindarajan Rex G Liu Thomas Serre 19 45 0 22 May 2020
Regularization Methods for Generative Adversarial Networks: An Overview of Recent Studies Minhyeok Lee Junhee Seok GAN 27 25 0 19 May 2020
An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learning Hirohisa Watanabe Mineto Tsukada Hiroki Matsutani 27 20 0 10 May 2020
Pores for thought: The use of generative adversarial networks for the stochastic reconstruction of 3D multi-phase electrode microstructures with periodic boundaries Andrea Gayon-Lombardo L. Mosser N. Brandon S. J. Cooper AI4CE 25 120 0 17 Feb 2020
REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild Rahul Duggal Scott Freitas Cao Xiao Duen Horng Chau Jimeng Sun 28 22 0 29 Jan 2020
Orthogonal Wasserstein GANs J. Müller Reinhard Klein Michael Weinmann 48 9 0 29 Nov 2019
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks Sekitoshi Kanai Yasutoshi Ida Yasuhiro Fujiwara Masanori Yamada S. Adachi AAML 23 1 0 19 Sep 2019
A Frobenius norm regularization method for convolutional kernels to avoid unstable gradient problem Pei-Chang Guo 34 5 0 25 Jul 2019
ReachNN: Reachability Analysis of Neural-Network Controlled Systems Chao Huang Jiameng Fan Wenchao Li Xin Chen Qi Zhu 31 78 0 25 Jun 2019
Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy Zhengwei Wang Qi She T. Ward MedIm EGVM 29 90 0 04 Jun 2019
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi 19 317 0 31 May 2019
Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness Adnan Siraj Rakin Zhezhi He Li Yang Yanzhi Wang Liqiang Wang Deliang Fan AAML 40 21 0 30 May 2019
An Empirical Study of Large-Batch Stochastic Gradient Descent with Structured Covariance Noise Yeming Wen Kevin Luk Maxime Gazeau Guodong Zhang Harris Chan Jimmy Ba ODL 25 22 0 21 Feb 2019
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 49 193 0 02 Oct 2018
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 16 15 0 30 Sep 2018
The Singular Values of Convolutional Layers Hanie Sedghi Vineet Gupta Philip M. Long FAtt 48 200 0 26 May 2018
NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations Marco Ciccone Marco Gallieri Jonathan Masci Christian Osendorfer Faustino J. Gomez 30 56 0 19 Apr 2018
L2-Nonexpansive Neural Networks Haifeng Qian M. Wegman 25 74 0 22 Feb 2018
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 56 4,402 0 16 Feb 2018
Gradient Regularization Improves Accuracy of Discriminative Models D. Varga Adrián Csiszárik Zsolt Zombori 18 53 0 28 Dec 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 310 2,896 0 15 Sep 2016
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 186 1,186 0 30 Nov 2014