This Matlab code provides implementations of the PSDMF algorithms described in the following papers. The key idea is that each subproblem is updated based on a phase retrieval or affine rank minimization algorithm.
- D. Lahat, Y. Lang, V. Y. F. Tan, and C. Févotte. Positive Semidefinite Matrix Factorization: A Connection with Phase Retrieval and Affine Rank Minimization. IEEE Transactions on Signal Processing, Vol. 69, 2021, pp. 3059--3074. [preprint] [paper]
- D. Lahat and C. Févotte. Positive semidefinite matrix factorization based on truncated Wirtinger flow. EUSIPCO, Amsterdam, The Netherlands, January 2021. Virtual format. [paper]
- D. Lahat and C. Févotte. Positive semidefinite matrix factorization: a link to phase retrieval and a block gradient algorithm. ICASSP, Barcelona, Spain, May 2020. Virtual format. [paper].