52 search results - page 4 / 11 » Probabilistic dyadic data analysis with local and global con... |
AAAI
2006
13 years 7 months ago
2006
Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...
IROS
2007
IEEE
14 years 2 days ago
2007
IEEE
— Local maps algorithms have demonstrated to be well suited for mapping large environments as can reduce the computational cost and improve the consistency of the final estimati...
ICML
2004
IEEE
14 years 6 months ago
2004
IEEE
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
RECOMB
2002
Springer
14 years 6 months ago
2002
Springer
This paper concerns the discovery of patterns in gene expression matrices, in which each element gives the expression level of a given gene in a given experiment. Most existing me...
NIPS
2003
13 years 7 months ago
2003
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...