Low-rank retractions: a survey and new results

P.-A. Absil () and I. Oseledets ()

Computational Optimization and Applications, 2015, vol. 62, issue 1, 5-29

Abstract: Retractions are a prevalent tool in Riemannian optimization that provides a way to smoothly select a curve on a manifold with given initial position and velocity. We review and propose several retractions on the manifold $${\mathcal {M}}_r$$ M r of rank- $$r$$ r $$m\times n$$ m × n matrices. With the exception of the exponential retraction (for the embedded geometry), which is clearly the least efficient choice, the retractions considered do not differ much in terms of run time and flop count. However, considerable differences are observed according to properties such as domain of definition, boundedness, first/second-order property, and symmetry. Copyright Springer Science+Business Media New York 2015

Keywords: Low-rank manifold; Fixed-rank manifold; Low-rank optimization; Retraction; Geodesic; Quasi-geodesic; Projective retraction; Orthographic retraction; Lie–Trotter splitting (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10589-014-9714-4

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