Latent Factor Analysis for High-Dimensional and Sparse Matrices: A Particle Swarm Optimization-Based Approach

by Ye Yuan

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Latent factor analysis models are an effective type of machine learning model for addressing high-dimensional and sparse matrices, which are encountered in many big-data-related industrial applications. The performance of a latent factor analysis model relies heavily on appropriate hyper-parameters. However, most hyper-parameters are data-dependent, and using grid-search to tune these hyper-parameters is truly laborious and expensive in computational...

Format:Paperback

Language:English

ISBN:9811967024

ISBN13:9789811967023

Release Date:November 2022

Publisher:Springer

Length:92 Pages

Weight:0.34 lbs.

Dimensions:0.2" x 6.1" x 9.2"

Related Subjects

Computers Computers & Technology Math Mathematics Science & Math

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Latent Factor Analysis for High-Dimensional and Sparse Matrices: A Particle Swarm Optimization-Based Approach

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