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IBPRIA
2005
Springer
13 years 10 months ago
Solving Particularization with Supervised Clustering Competition Scheme
The process of mixing labelled and unlabelled data is being recently studied in semi-supervision techniques. However, this is not the only scenario in which mixture of labelled and...
Oriol Pujol, Petia Radeva
SCALESPACE
2007
Springer
13 years 11 months ago
Fuzzy Region Competition: A Convex Two-Phase Segmentation Framework
This paper introduces a new framework for two-phase image segmentation, namely the Fuzzy Region Competition. A generic formulation is developed that extends in a convex way several...
Benoit Mory, Roberto Ardon
CVPR
2009
IEEE
15 years 8 days ago
Regularized Multi-Class Semi-Supervised Boosting
Many semi-supervised learning algorithms only deal with binary classification. Their extension to the multi-class problem is usually obtained by repeatedly solving a set of bina...
Amir Saffari, Christian Leistner, Horst Bischof
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
14 years 5 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
ICML
2008
IEEE
14 years 5 months ago
ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...