Decentralized Rank-Adaptive Matrix Factorization-Part I: Algorithm Development

Factorizing a low-rank matrix into two matrix factors with low dimensions from its noisy observations is a classical but challenging problem arising from real-world applications. This paper develops decentralized matrix factorization algorithms, i.e., factorizing a matrix whose columns are stored di...

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Bibliographic Details
Published in:IEEE transactions on signal processing Vol. 73; pp. 4124 - 4140
Main Authors: Jiao, Yuchen, Gu, Yuantao, Chang, Tsung-Hui, Luo, Zhi-Quan
Format: Journal Article
Language:English
Published: New York IEEE 2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1053-587X, 1941-0476
Online Access:Get full text
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