1825 search results - page 5 / 365 » Local Dimensionality Reduction |
101
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CVPR
2008
IEEE
16 years 3 months ago
2008
IEEE
We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...
119
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COMPLIFE
2006
Springer
15 years 4 months ago
2006
Springer
We present a method for simultaneous dimension reduction and metastability analysis of high dimensional time series. The approach is based on the combination of hidden Markov model...
117
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ICPR
2006
IEEE
16 years 2 months ago
2006
IEEE
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
151
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CVPR
2009
IEEE
16 years 8 months ago
2009
IEEE
Non-linear dimensionality reductionmethods are powerful techniques to deal with
high-dimensional datasets. However, they often are susceptible to local minima
and perform poorly ...
102
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ICML
2007
IEEE
16 years 1 months ago
2007
IEEE
This paper presents a Local Learning Projection (LLP) approach for linear dimensionality reduction. We first point out that the well known Principal Component Analysis (PCA) essen...