50 search results - page 5 / 10 » Learning Semi-Riemannian Metrics for Semisupervised Feature ... |
COLING
2010
13 years 22 days ago
2010
Several researchers have proposed semi-supervised learning methods for adapting event extraction systems to new event types. This paper investigates two kinds of bootstrapping met...
ISNN
2011
Springer
12 years 8 months ago
2011
Springer
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
CIKM
2008
Springer
13 years 7 months ago
2008
Springer
In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
ICCV
2007
IEEE
14 years 7 months ago
2007
IEEE
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The projection vectors are commonly obtained by maximizing ...
PAKDD
2009
ACM
14 years 16 days ago
2009
ACM
Abstract. Clustering high dimensional data with sparse features is challenging because pairwise distances between data items are not informative in high dimensional space. To addre...