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Max-plus Operators Applied to Filter Selection and Model Pruning in
  Neural Networks

Max-plus Operators Applied to Filter Selection and Model Pruning in Neural Networks

19 March 2019
Yunxiang Zhang
S. Blusseau
Santiago Velasco-Forero
Isabelle Bloch
Jesús Angulo
ArXivPDFHTML

Papers citing "Max-plus Operators Applied to Filter Selection and Model Pruning in Neural Networks"

3 / 3 papers shown
Title
Going beyond p-convolutions to learn grayscale morphological operators
Going beyond p-convolutions to learn grayscale morphological operators
Alexandre Kirszenberg
Guillaume Tochon
Élodie Puybareau
Jesús Angulo
AI4CE
8
13
0
19 Feb 2021
Sparse Approximate Solutions to Max-Plus Equations with Application to
  Multivariate Convex Regression
Sparse Approximate Solutions to Max-Plus Equations with Application to Multivariate Convex Regression
Nikos Tsilivis
Anastasios Tsiamis
Petros Maragos
29
3
0
06 Nov 2020
A Universal Approximation Result for Difference of log-sum-exp Neural
  Networks
A Universal Approximation Result for Difference of log-sum-exp Neural Networks
G. Calafiore
S. Gaubert
Member
C. Possieri
11
44
0
21 May 2019
1