methodology-20
Low-Rank Matrix Completion
3260 papers • 126 benchmarks • 313 datasets
Low-Rank Matrix Completion is an important problem with several applications in areas such as recommendation systems, sketching, and quantum tomography. The goal in matrix completion is to recover a low rank matrix, given a small number of entries of the matrix. Source: Universal Matrix Completion
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