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GrassmannOptim: AnRPackage for Grassmann Manifold Optimization
Author(s) -
Kofi P. Adragni,
R. Dennis Cook,
Seongho Wu
Publication year - 2012
Publication title -
journal of statistical software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.636
H-Index - 145
ISSN - 1548-7660
DOI - 10.18637/jss.v050.i05
Subject(s) - manifold (fluid mechanics) , optimization problem , grassmannian , invariant manifold , function (biology) , invariant (physics) , combinatorics , mathematics , vector optimization , variety (cybernetics) , computer science , mathematical optimization , algorithm , pure mathematics , artificial intelligence , multi swarm optimization , mathematical physics , mechanical engineering , evolutionary biology , engineering , biology
The optimization of a real-valued objective function f(U), where U is a p X d,p > d, semi-orthogonal matrix such that UTU=Id, and f is invariant under right orthogonal transformation of U, is often referred to as a Grassmann manifold optimization. Manifold optimization appears in a wide variety of computational problems in the applied sciences. In this article, we present GrassmannOptim, an R package for Grassmann manifold optimization. The implementation uses gradient-based algorithms and embeds a stochastic gradient method for global search. We describe the algorithms, provide some illustrative examples on the relevance of manifold optimization and finally, show some practical usages of the package.

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