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COOPIS
2004
IEEE
15 years 5 months ago
Learning Classifiers from Semantically Heterogeneous Data
Semantically heterogeneous and distributed data sources are quite common in several application domains such as bioinformatics and security informatics. In such a setting, each dat...
Doina Caragea, Jyotishman Pathak, Vasant Honavar
117
Voted
BMVC
2010
14 years 11 months ago
StyP-Boost: A Bilinear Boosting Algorithm for Learning Style-Parameterized Classifiers
We introduce a novel bilinear boosting algorithm, which extends the multi-class boosting framework of JointBoost to optimize a bilinear objective function. This allows style param...
Jonathan Warrell, Philip H. S. Torr, Simon Prince
CVPR
2009
IEEE
16 years 8 months ago
A Min-Max Framework of Cascaded Classifier with Multiple Instance Learning for Computer Aided Diagnosis
The computer aided diagnosis (CAD) problems of detecting potentially diseased structures from medical images are typically distinguished by the following challenging characterist...
Dijia Wu (Rensselaer Polytechnic Institute), Jinbo...
WWW
2008
ACM
16 years 2 months ago
Learning to classify short and sparse text & web with hidden topics from large-scale data collections
This paper presents a general framework for building classifiers that deal with short and sparse text & Web segments by making the most of hidden topics discovered from larges...
Xuan Hieu Phan, Minh Le Nguyen, Susumu Horiguchi
IJDMB
2007
110views more  IJDMB 2007»
15 years 1 months ago
Transductive learning with EM algorithm to classify proteins based on phylogenetic profiles
: Phylogenetic profiles of proteins  strings of ones and zeros encoding respectively the presence and absence of proteins in a group of genomes  have recently been used to id...
Roger A. Craig, Li Liao