HIGHLIGHTS
- who: Mandi Liu and collaborators from the Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA have published the Article: Bayesian Matrix Learning by Principle Eigenvector for Completing Missing Medical Data, in the Journal: (JOURNAL)
- what: The research on missing value completion in the existing literature mainly focuses on the low-rank matrix completion methods: Trever Hastie et_al applied low-rank SVD to advance the current matrix completion algorithms and developed a new algorithm that can deal with the Netflix competition data . The authors aim for a specific algorithm to . . .
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