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Structured Low-Rank Approximation as Optimization on a Grassmann Manifold
Konstantin Usevich
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Oznake: computer science;optimization methods;machine learning;kernel methods;support vector machines;compressed sensing;regularization
Many data modeling problems can be posed and solved as a structured low-rank approximation problem. Using the variable projection approach, the problem is reformulated as optimization on a Grassmann manifold. We compare local optimization methods based on different parametrizations of the manifold, ...
Leto: 2013 Vir: videolectures.net
Št. zadetkov: 1
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