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Latent Factor Analysis for High-Dimensional and Sparse Matrices: A Particle Swarm Optimization-Based Approach
Paperback
Series: Springerbriefs in Computer Science
General ComputersProbability & Statistics
ISBN13: 9789811967023
Publisher: Springer Nature
Published: Nov 16 2022
Pages: 92
Weight: 0.34
Height: 0.21 Width: 6.14 Depth: 9.21
Language: English
This is the first book to focus on how particle swarm optimization can be incorporated into latent factor analysis for efficient hyper-parameter adaptation, an approach that offers high scalability in real-world industrial applications.
The book will help students, researchers and engineers fully understand the basic methodologies of hyper-parameter adaptation via particle swarm optimization in latent factor analysis models. Further, it will enable them to conduct extensive research and experiments on the real-world applications of the content discussed.
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