Optimal approximation of piecewise smooth functions using deep ReLU neural networks

We study the necessary and sufficient complexity of ReLU neural networks – in terms of depth and number of weights – which is required for approximating classifier functions in an Lp-sense. As a model class, we consider the set Eβ(Rd) of possibly discontinuous piecewise Cβ functions f:[−12,12]d→R, w...

Celý popis

Podrobná bibliografia

Vydané v:	Neural networks Ročník 108; s. 296 - 330
Hlavní autori:	Petersen, Philipp, Voigtlaender, Felix
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Ltd 01.12.2018
Predmet:	Curse of dimension Deep neural networks Function approximation Metric entropy Neural Networks (Computer) Piecewise smooth functions Sparse connectivity Deep neural networks Function approximation Curse of dimension Metric entropy Piecewise smooth functions Sparse connectivity
ISSN:	0893-6080, 1879-2782, 1879-2782
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!