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Matrix Completion
Matrix Completion is a method for estimating missing or unknown data from a low-rank matrix of known data, aiming to recover lost information. This approach originates from machine learning and is particularly useful for dealing with highly sparse matrices, making it valuable in applications such as recommendation systems and image processing.
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