159 search results - page 13 / 32 » Sparse non-Gaussian component analysis |
ICDM
2010
IEEE
13 years 6 months ago
2010
IEEE
Abstract--Randomization is a general technique for evaluating the significance of data analysis results. In randomizationbased significance testing, a result is considered to be in...
NIPS
2008
13 years 10 months ago
2008
We present a generative model for performing sparse probabilistic projections, which includes sparse principal component analysis and sparse canonical correlation analysis as spec...
NIPS
2007
13 years 10 months ago
2007
An important problem in many fields is the analysis of counts data to extract meaningful latent components. Methods like Probabilistic Latent Semantic Analysis (PLSA) and Latent ...
SIAMJO
2011
13 years 3 months ago
2011
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
JACM
2011
12 years 11 months ago
2011
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component i...