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Unveiling the Power of Sparse Neural Networks for Feature Selection

Unveiling the Power of Sparse Neural Networks for Feature Selection

8 August 2024
Zahra Atashgahi
Tennison Liu
Mykola Pechenizkiy
Raymond N. J. Veldhuis
D. Mocanu
M. Schaar
ArXivPDFHTML

Papers citing "Unveiling the Power of Sparse Neural Networks for Feature Selection"

4 / 4 papers shown
Title
RelChaNet: Neural Network Feature Selection using Relative Change Scores
RelChaNet: Neural Network Feature Selection using Relative Change Scores
Felix Zimmer
24
0
0
03 Oct 2024
Composite Feature Selection using Deep Ensembles
Composite Feature Selection using Deep Ensembles
F. Imrie
Alexander Norcliffe
Pietro Lio'
M. Schaar
42
11
0
01 Nov 2022
Sparsity in Deep Learning: Pruning and growth for efficient inference
  and training in neural networks
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
Torsten Hoefler
Dan Alistarh
Tal Ben-Nun
Nikoli Dryden
Alexandra Peste
MQ
141
684
0
31 Jan 2021
Feature Importance Ranking for Deep Learning
Feature Importance Ranking for Deep Learning
Maksymilian Wojtas
Ke Chen
139
116
0
18 Oct 2020
1