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126
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DIS
2009
Springer
15 years 10 months ago
MICCLLR: Multiple-Instance Learning Using Class Conditional Log Likelihood Ratio
Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
Yasser El-Manzalawy, Vasant Honavar
144
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FUIN
2002
123views more  FUIN 2002»
15 years 3 months ago
Learning Rough Set Classifiers from Gene Expressions and Clinical Data
Biological research is currently undergoing a revolution. With the advent of microarray technology the behavior of thousands of genes can be measured simultaneously. This capabilit...
Herman Midelfart, Henryk Jan Komorowski, Kristin N...
142
Voted
ICDM
2008
IEEE
193views Data Mining» more  ICDM 2008»
15 years 10 months ago
Multiplicative Mixture Models for Overlapping Clustering
The problem of overlapping clustering, where a point is allowed to belong to multiple clusters, is becoming increasingly important in a variety of applications. In this paper, we ...
Qiang Fu, Arindam Banerjee
ICIP
2005
IEEE
16 years 5 months ago
Local manifold matching for face recognition
In this paper, we propose a novel classification method, called local manifold matching (LMM), for face recognition. LMM has great representational capacity of available prototypes...
Wei Liu, Wei Fan, Yunhong Wang, Tieniu Tan
128
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LREC
2008
174views Education» more  LREC 2008»
15 years 5 months ago
UnsuParse: unsupervised Parsing with unsupervised Part of Speech Tagging
Based on simple methods such as observing word and part of speech tag co-occurrence and clustering, we generate syntactic parses of sentences in an entirely unsupervised and self-...
Christian Hänig, Stefan Bordag, Uwe Quasthoff