502 search results - page 26 / 101 » Principal Component Analysis for Sparse High-Dimensional Dat... |
ICDM
2007
IEEE
14 years 19 days ago
2007
IEEE
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
ICA
2007
Springer
14 years 19 days ago
2007
Springer
Abstract. A nonparametric Bayesian extension of Independent Components Analysis (ICA) is proposed where observed data Y is modelled as a linear superposition, G, of a potentially i...
ICANN
1997
Springer
14 years 10 days ago
1997
Springer
Abstract. In this paper we compare two methods for intrinsic dimensionality (ID) estimation based on optimally topology preserving maps (OTPMs). The rst one is a direct approach, w...
ADBIS
2003
Springer
14 years 2 months ago
2003
Springer
Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble...
ICASSP
2010
IEEE
13 years 9 months ago
2010
IEEE
Recently, the Sparse Matrix Transform (SMT) has been proposed as a tool for estimating the eigen-decomposition of high dimensional data vectors [1]. The SMT approach has two major...