KDD
2012
ACM
11 years 7 months ago
2012
ACM
Building an accurate emerging pattern classifier with a highdimensional dataset is a challenging issue. The problem becomes even more difficult if the whole feature space is unava...
KDD
2012
ACM
11 years 7 months ago
2012
ACM
The prevalent use of social media produces mountains of unlabeled, high-dimensional data. Feature selection has been shown eļ¬ective in dealing with high-dimensional data for eļ¬...
CLEF
2010
Springer
13 years 5 months ago
2010
Springer
Abstract. This paper describes our approach to the Person Name Disambiguation clustering task in the Third Web People Search Evaluation Campaign(WePS3). The method focuses on two a...
CISST
2004
13 years 6 months ago
2004
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
DAGM
2009
Springer
13 years 11 months ago
2009
Springer
The human ability to learn diļ¬cult object categories from just a few views is often explained by an extensive use of knowledge from related classes. In this work we study the use...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...