1825 search results - page 5 / 365 » Local Dimensionality Reduction |
CVPR
2008
IEEE
15 years 26 days 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...
COMPLIFE
2006
Springer
14 years 2 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...
ICPR
2006
IEEE
14 years 12 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...
CVPR
2009
IEEE
15 years 6 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 ...
ICML
2007
IEEE
14 years 11 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...