93 search results - page 13 / 19 » Supervised probabilistic principal component analysis |
FTML
2010
13 years 6 months ago
2010
We give a tutorial overview of several geometric methods for dimension reduction. We divide the methods into projective methods and methods that model the manifold on which the da...
JCP
2008
13 years 7 months ago
2008
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
SIGIR
2008
ACM
13 years 7 months ago
2008
ACM
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
NIPS
2008
13 years 9 months ago
2008
Principal Components Analysis (PCA) has become established as one of the key tools for dimensionality reduction when dealing with real valued data. Approaches such as exponential ...
NIPS
2003
13 years 9 months ago
2003
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...