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• W1896519906 abstract "The optimization of a real-valued objective function <i>f</i>(<b>U</b>), where <b>U</b> is a <i>p</i> X <i>d,p</i> > <i>d</i>, semi-orthogonal matrix such that <b>U</b>^T<b>U</b>=<b>I</b>_d, and <i>f</i> is invariant under right orthogonal transformation of <b>U</b>, 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 <b>GrassmannOptim</b>, 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." @default.
• W1896519906 created "2016-06-24" @default.
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• W1896519906 date "2012-01-01" @default.
• W1896519906 modified "2023-10-18" @default.
• W1896519906 title "<b>GrassmannOptim</b>: An<i>R</i>Package for Grassmann Manifold Optimization" @default.
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• W1896519906 doi "https://doi.org/10.18637/jss.v050.i05" @default.
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