Concurrent Training and Layer Pruning of Deep Neural Networks

We propose an algorithm capable of identifying and eliminating irrelevant layers of a neural network during the early stages of training. In contrast to weight or filter-level pruning, layer pruning reduces the harder to parallelize sequential computation of a neural network. We employ a structure u...

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Veröffentlicht in:	arXiv.org 2024-06
Hauptverfasser:	Valentin Frank Ingmar Guenter, Sideris, Athanasios
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Computational efficiency Computing costs Convergence Cost control Inference Information flow Machine learning Neural networks Parameters Random variables
Online-Zugang:	Volltext
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