298 search results - page 28 / 60 » Subspace Clustering of High Dimensional Data |
126
Voted
JMLR
2012
13 years 2 months ago
2012
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
103
Voted
AAAI
2007
15 years 2 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...
125
Voted
TKDE
2010
14 years 7 months ago
2010
The sparse data is becoming increasingly common and available in many real-life applications. However, relative little attention has been paid to effectively model the sparse data ...
ICDM
2006
IEEE
15 years 6 months ago
2006
IEEE
High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to...
CVPR
2008
IEEE
16 years 2 months ago
2008
IEEE
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...