58 search results - page 4 / 12 » Principal Component Analysis with Contaminated Data: The Hig... |
NIPS
2003
13 years 7 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 ...
ICMLA
2008
13 years 7 months ago
2008
In this paper we describe an interdisciplinary collaboration between researchers in machine learning and oceanography. The collaboration was formed to study the problem of open oc...
APWEB
2006
Springer
13 years 9 months ago
2006
Springer
Clustering is to identify densely populated subgroups in data, while correlation analysis is to find the dependency between the attributes of the data set. In this paper, we combin...
CSB
2003
IEEE
13 years 11 months ago
2003
IEEE
The problem of clustering continuous valued data has been well studied in literature. Its application to microarray analysis relies on such algorithms as -means, dimensionality re...
AAAI
2007
13 years 8 months ago
2007
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...