Laor Initialization: A New Weight Initialization Method for the Backpropagation of Deep Learning

This paper presents Laor Initialization, an innovative weight initialization technique for deep neural networks that utilizes forward-pass error feedback in conjunction with k-means clustering to optimize the initial weights. In contrast to traditional methods, Laor adopts a data-driven approach tha...

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Bibliografske podrobnosti

Principais autores:	Laor Boongasame, Jirapond Muangprathub, Karanrat Thammarak
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2025-07-01
Serija:	Big Data and Cognitive Computing
Teme:	Laor Initialization weight initialization deep learning neural network k-means clustering
Online dostop:	https://www.mdpi.com/2504-2289/9/7/181
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