Enhanced Matrix Completion with Manifold Learning

We study the problem of matrix completion when infor- mation about row or column proximities is available, in the form of weighted graphs. The problem can be formulated as the optimization of a convex function that can be solved efficiently using the alternating direction multipliers method. Experiments show that our model offers better reconstruction than the standard method that only uses a low rank assumption, especially when few observations are available.


Presented at:
International BASP Frontiers Workshop 2015, Villars-sur-Ollon, Switzerland, January 25 - 30, 2015
Year:
2015
Laboratories:




 Record created 2015-01-27, last modified 2018-03-17

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