88 search results - page 13 / 18 » Distance Preserving Dimension Reduction for Manifold Learnin... |
AAAI
2006
14 years 10 months ago
2006
Over the past few years, some embedding methods have been proposed for feature extraction and dimensionality reduction in various machine learning and pattern classification tasks...
COLT
2008
Springer
14 years 11 months ago
2008
Springer
An algorithm is presented for online learning of rotations. The proposed algorithm involves matrix exponentiated gradient updates and is motivated by the von Neumann divergence. T...
109
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ICASSP
2011
IEEE
14 years 1 months ago
2011
IEEE
The Restricted Isometry Property (RIP) is an important concept in compressed sensing. It is well known that many random matrices satisfy the RIP with high probability, whenever th...
ESANN
2007
14 years 11 months ago
2007
Local algorithms for non-linear dimensionality reduction [1], [2], [3], [4], [5] and semi-supervised learning algorithms [6], [7] use spectral decomposition based on a nearest neig...
101
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ICASSP
2011
IEEE
14 years 1 months ago
2011
IEEE
We present a polytope-kernel density estimation (PKDE) methodology that allows us to perform exact mean-shift updates along the edges of the Delaunay graph of the data. We discuss...