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Claudia Giesbert

Bin Gao (WWU): A Riemannian rank-adaptive method for low-rank matrix completion

Wednesday, 17.11.2021 14:00 im Raum M5

Mathematik und Informatik

In this talk, we consider the low-rank matrix completion problem which has been extensively studied in recent years. This problem can be solved by Riemannian optimization on a fixed-rank manifold. However, a drawback of the known approaches is that the rank parameter has to be fixed a priori. Instead, we consider the optimization problem on the set of bounded-rank matrices. We propose a Riemannian rank-adaptive method, which consists of fixed-rank optimization, rank increase step and rank reduction step. We explore its performance applied to the low-rank matrix completion problem. Numerical experiments on synthetic and real-world datasets illustrate that the proposed rank-adaptive method compares favorably with state-of-the-art algorithms. This is a joint work with P.-A. Absil.



Angelegt am 14.10.2021 von Claudia Giesbert
Geändert am 16.11.2021 von Frank Wübbeling
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Angewandte Mathematik Münster
Oberseminar Angewandte Mathematik