AI RESEARCH
A Complete Loss Landscape Analysis of Regularized Deep Matrix Factorization
arXiv CS.LG
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ArXi:2506.20344v3 Announce Type: replace-cross Despite its wide range of applications across various domains, the optimization foundations of deep matrix factorization (DMF) remain largely open. In this work, we aim to fill this gap by conducting a comprehensive study of the loss landscape of the regularized DMF problem. Toward this goal, we first provide a closed-form characterization of all critical points of the problem.