Matrix Optimization Over Low-Rank Spectral Sets: Stationary Points and Local and Global Minimizers
نویسندگان
چکیده
منابع مشابه
Low-rank spectral optimization
Various applications in signal processing and machine learning give rise to highly structured spectral optimization problems characterized by low-rank solutions. Two important examples that motivate this work are optimization problems from phase retrieval and from blind deconvolution, which are designed to yield rank-1 solutions. An algorithm is described based on solving a certain constrained ...
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ژورنال
عنوان ژورنال: Journal of Optimization Theory and Applications
سال: 2019
ISSN: 0022-3239,1573-2878
DOI: 10.1007/s10957-019-01606-8