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103
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ICPR
2008
IEEE
16 years 3 months ago
Supervised learning of a generative model for edge-weighted graphs
This paper addresses the problem of learning archetypal structural models from examples. To this end we define a generative model for graphs where the distribution of observed nod...
Andrea Torsello, David L. Dowe
100
Voted
ICDM
2008
IEEE
112views Data Mining» more  ICDM 2008»
15 years 9 months ago
Supervised Inductive Learning with Lotka-Volterra Derived Models
We present a classification algorithm built on our adaptation of the Generalized Lotka-Volterra model, well-known in mathematical ecology. The training algorithm itself consists ...
Karen Hovsepian, Peter Anselmo, Subhasish Mazumdar
126
Voted
CCIA
2005
Springer
15 years 8 months ago
On the usefulness of supervised learning for vessel border detection in IntraVascular Imaging
IntraVascular UltraSound (IVUS) imaging is a useful tool in diagnosis of cardiac diseases since sequences completely show the morphology of coronary vessels. Vessel borders detecti...
Aura Hernandez, Debora Gil, Petia Radeva
NIPS
2004
15 years 4 months ago
Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning
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...
Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, Jo...
IJCAI
2003
15 years 4 months ago
Semi-Supervised Learning with Explicit Misclassification Modeling
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
Massih-Reza Amini, Patrick Gallinari