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» Co-Tracking Using Semi-Supervised Support Vector Machines
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ICML
2005
IEEE
16 years 6 months ago
Learning class-discriminative dynamic Bayesian networks
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
John Burge, Terran Lane
ICML
2005
IEEE
16 years 6 months ago
Supervised versus multiple instance learning: an empirical comparison
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Soumya Ray, Mark Craven
ICML
2004
IEEE
16 years 6 months ago
SVM-based generalized multiple-instance learning via approximate box counting
The multiple-instance learning (MIL) model has been very successful in application areas such as drug discovery and content-based imageretrieval. Recently, a generalization of thi...
Qingping Tao, Stephen D. Scott, N. V. Vinodchandra...
ICML
2000
IEEE
16 years 6 months ago
Duality and Geometry in SVM Classifiers
We develop an intuitive geometric interpretation of the standard support vector machine (SVM) for classification of both linearly separable and inseparable data and provide a rigo...
Kristin P. Bennett, Erin J. Bredensteiner
BMCBI
2007
162views more  BMCBI 2007»
15 years 6 months ago
Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis
Background: Genome-wide identification of specific oligonucleotides (oligos) is a computationallyintensive task and is a requirement for designing microarray probes, primers, and ...
Chun-Chi Liu, Chin-Chung Lin, Ker-Chau Li, Wen-Shy...