540 search results - page 8 / 108 » Dimensionality Reduction for Data in Multiple Feature Repres... |
98
Voted
PR
2011
14 years 10 days ago
2011
Increasingly large amount of multidimensional data are being generated on a daily basis in many applications. This leads to a strong demand for learning algorithms to extract usef...
TKDE
2008
14 years 9 months ago
2008
The linear discriminant analysis (LDA) technique is very popular in pattern recognition for dimensionality reduction. It is a supervised learning technique that finds a linear tran...
AAAI
2008
14 years 12 months ago
2008
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the train...
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
We consider feature extraction (dimensionality reduction) for compositional data, where the data vectors are constrained to be positive and constant-sum. In real-world problems, t...
NIPS
2004
14 years 11 months ago
2004
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional d...