Near-isometric linear embeddings of manifolds

IEEE Signal Processing Workshop on Statistical Signal Processing
Volume: 2012, Pages: 728 - 731
Published: Oct 4, 2012
Abstract
We propose a new method for linear dimensionality reduction of manifold-modeled data. Given a training set X of Q points belonging to a manifoldM ⊂ R , we construct a linear operator P : R → R that approximately preserves the norms of all ` Q 2 null pairwise difference vectors (or secants) of X . We design the matrix P via a trace-norm minimization that can be efficiently solved as a semi-definite program (SDP). When X comprises a sufficiently...
Paper Details
Title
Near-isometric linear embeddings of manifolds
DOI
Published Date
Oct 4, 2012
Journal
Volume
2012
Pages
728 - 731
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