403 search results - page 20 / 81 » Metric and Kernel Learning Using a Linear Transformation |
116
click to vote
ICML
2009
IEEE
16 years 2 months ago
2009
IEEE
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
119
click to vote
IJCAI
2007
15 years 3 months ago
2007
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
134
click to vote
PKDD
2010
Springer
15 years 7 days ago
2010
Springer
Abstract. The eigenspectrum of a graph Laplacian encodes smoothness information over the graph. A natural approach to learning involves transforming the spectrum of a graph Laplaci...
114
click to vote
CORR
2007
Springer
15 years 1 months ago
2007
Springer
We consider the least-square regression problem with regularization by a block 1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, r...
128
Voted
CORR
2006
Springer
15 years 1 months ago
2006
Springer
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...