Linear Convergence of a Proximal Alternating Minimization Method with Extrapo…
A popular robust alternative of the classic principal component analysis (PCA) is the -norm PCA (L1-PCA), which aims to find a subspace that captures the most variation in a dataset as measured by…
Weakly Convex Optimization Over Stiefel Manifold Using Riemannian Subgradient…
We consider a class of nonsmooth optimization problems over the Stiefel manifold, in which the objective function is weakly convex in the ambient Euclidean space. Such problems are ubiquitous in en…
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