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Poster

Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity

Ron Fisher · Dan Garber

Hall J (level 1) #837

Keywords: [ Low-Rank ] [ first-order methods ] [ Subspace Recovery ] [ strict complementarity ] [ frank-wolfe ] [ Convex Optimization ] [ principal component analysis ] [ nonconvex optimization ] [ robust PCA ]

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Abstract: We consider optimization problems in which the goal is to find a $k$-dimensional subspace of $\mathbb{R}^n$, $k<

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