Incremental and Parallel Machine Learning Algorithms with Automated Learning Rate Adjustments

The existing machine learning algorithms for minimizing the convex function over a closed convex set suffer from slow convergence because their learning rates must be determined before running them. This paper proposes two machine learning algorithms incorporating the line search method, which autom...

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Veröffentlicht in:	arXiv.org
Hauptverfasser:	Hishinuma, Kazuhiro, Iiduka, Hideaki
Format:	Paper
Sprache:	Englisch
Veröffentlicht:	Ithaca Cornell University Library, arXiv.org 09.08.2019
Schlagworte:	Algorithms Computational geometry Convex analysis Convexity Hilbert space Iterative methods Microprocessors Optimization Run time (computers) Search methods
ISSN:	2331-8422
Online-Zugang:	Volltext
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