12 search results - page 2 / 3 » Spectral Regularization Algorithms for Learning Large Incomp... |
ICDE
2008
IEEE
14 years 6 months ago
2008
IEEE
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. It has been widely used in many fields of information proces...
ICPR
2008
IEEE
14 years 5 months ago
2008
IEEE
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
KDD
2008
ACM
14 years 5 months ago
2008
ACM
A hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set. It has been applied successfully to capture highord...
SDM
2007
SIAM
13 years 6 months ago
2007
SIAM
Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
NIPS
2004
13 years 6 months ago
2004
We present an algorithm based on convex optimization for constructing kernels for semi-supervised learning. The kernel matrices are derived from the spectral decomposition of grap...