An Overview of Low-Rank Matrix Recovery From Incomplete Observations
作者： Mark A. Davenport , Justin Romberg
DOI: 10.1109/JSTSP.2016.2539100
关键词: Non-negative matrix factorization 、 Theoretical computer science 、 Matrix (mathematics) 、 Field (computer science) 、 Signal processing 、 Sparse matrix 、 Matrix decomposition 、 Low-rank approximation 、 Mathematics 、 Context (language use)
摘要: Low-rank matrices play a fundamental role in modeling and computational methods for signal processing and machine learning. In many applications where low-rank matrices …
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