Shakeout: A New Approach to Regularized Deep Neural Network Training

13 April 2019

Papers citing "Shakeout: A New Approach to Regularized Deep Neural Network Training"

8 / 8 papers shown

Title
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 35 2 0 04 Jan 2021
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 36 79 0 17 Sep 2020
Contrastive Adaptation Network for Unsupervised Domain Adaptation Guoliang Kang Lu Jiang Yi Yang Alexander G. Hauptmann 14 826 0 04 Jan 2019
PANDA: AdaPtive Noisy Data Augmentation for Regularization of Undirected Graphical Models Yinan Li Xiao Liu Fang Liu 29 7 0 11 Oct 2018
MPDCompress - Matrix Permutation Decomposition Algorithm for Deep Neural Network Compression Lazar Supic R. Naous Ranko Sredojevic Aleksandra Faust Vladimir M. Stojanović 19 4 0 30 May 2018
Excitation Dropout: Encouraging Plasticity in Deep Neural Networks Andrea Zunino Sarah Adel Bargal Pietro Morerio Jianming Zhang Stan Sclaroff Vittorio Murino 21 23 0 23 May 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,639 0 03 Jul 2012