Paper ID sheet UCL-INMA-2018.09
- Title
-
Preconditioned conjugate gradient algorithms for graph regularized matrix completion
- Authors
- Shuyu Dong, P.-A. Absil, Kyle A. Gallivan
- Abstract
-
Low-rank matrix completion is the problem of recovering
the missing entries of a data matrix by using the assumption that a good
low-rank approximation to the true matrix is possible. Much attention has
been paid recently to exploiting correlations between the column/row enti-
ties through side information to improve the matrix completion quality. In
this paper, we propose an effcient algorithm for solving the low-rank ma-
trix completion with graph-based regularizers. Experiments on synthetic
data show that our approach achieves significant speedup compared to the
alternating minimization scheme.
- Key words
-
- Status
- Proceedings of the ESANN 2019 conference, to appear
- Download
-
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