E2E-FS: An End-to-End Feature Selection Method for Neural Networks

14 December 2020

Papers citing "E2E-FS: An End-to-End Feature Selection Method for Neural Networks"

12 / 12 papers shown

Title
Infinite Feature Selection: A Graph-based Feature Filtering Approach Giorgio Roffo Simone Melzi U. Castellani Alessandro Vinciarelli Marco Cristani 58 109 0 15 Jun 2020
Importance Estimation for Neural Network Pruning Pavlo Molchanov Arun Mallya Stephen Tyree I. Frosio Jan Kautz 3DPC 73 879 0 25 Jun 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan Quoc V. Le 3DV MedIm 129 18,058 0 28 May 2019
A scalable saliency-based Feature selection method with instance level information Brais Cancela V. Bolón-Canedo Amparo Alonso-Betanzos João Gama FAtt 43 13 0 30 Apr 2019
Concrete Autoencoders for Differentiable Feature Selection and Reconstruction Abubakar Abid M. F. Balin James Zou SyDa 47 225 0 27 Jan 2019
AutoShuffleNet: Learning Permutation Matrices via an Exact Lipschitz Continuous Penalty in Deep Convolutional Neural Networks J. Lyu Shuai Zhang Y. Qi Jack Xin 48 27 0 24 Jan 2019
Learning to Explain: An Information-Theoretic Perspective on Model Interpretation Jianbo Chen Le Song Martin J. Wainwright Michael I. Jordan MLT FAtt 129 572 0 21 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 233 8,856 0 25 Aug 2017
Infinite Latent Feature Selection: A Probabilistic Latent Graph-Based Ranking Approach Giorgio Roffo Simone Melzi U. Castellani Alessandro Vinciarelli BDL 33 212 0 24 Jul 2017
Wide Residual Networks Sergey Zagoruyko N. Komodakis 299 7,971 0 23 May 2016
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 407 43,234 0 11 Feb 2015
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 255 7,279 0 20 Dec 2013