methodology-20
Matrix Completion
3260 papers • 126 benchmarks • 313 datasets
Matrix Completion is a method for recovering lost information. It originates from machine learning and usually deals with highly sparse matrices. Missing or unknown data is estimated using the low-rank matrix of the known data. Source: A Fast Matrix-Completion-Based Approach for Recommendation Systems
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