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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 8 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
KDD
2004
ACM
114views Data Mining» more  KDD 2004»
14 years 8 months ago
Mining reference tables for automatic text segmentation
Automatically segmenting unstructured text strings into structured records is necessary for importing the information contained in legacy sources and text collections into a data ...
Eugene Agichtein, Venkatesh Ganti
ECML
2006
Springer
13 years 11 months ago
Margin-Based Active Learning for Structured Output Spaces
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
Dan Roth, Kevin Small
MICCAI
2010
Springer
13 years 6 months ago
Agreement-Based Semi-supervised Learning for Skull Stripping
Abstract. Learning-based approaches have become increasingly practical in medical imaging. For a supervised learning strategy, the quality of the trained algorithm (usually a class...
Juan Eugenio Iglesias, Cheng-Yi Liu, Paul M. Thomp...
HAIS
2010
Springer
13 years 5 months ago
Reducing Dimensionality in Multiple Instance Learning with a Filter Method
In this article, we describe a feature selection algorithm which can automatically find relevant features for multiple instance learning. Multiple instance learning is considered a...
Amelia Zafra, Mykola Pechenizkiy, Sebastián...