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» An fMRI Activation Method Using Complex Data
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BIBE
2009
IEEE
131views Bioinformatics» more  BIBE 2009»
15 years 3 months ago
Learning Scaling Coefficient in Possibilistic Latent Variable Algorithm from Complex Diagnosis Data
—The Possibilistic Latent Variable (PLV) clustering algorithm is a powerful tool for the analysis of complex datasets due to its robustness toward data distributions of different...
Zong-Xian Yin
ICCV
2007
IEEE
16 years 1 months ago
Structure from Statistics - Unsupervised Activity Analysis using Suffix Trees
Models of activity structure for unconstrained environments are generally not available a priori. Recent representational approaches to this end are limited by their computational...
Raffay Hamid, Siddhartha Maddi, Aaron F. Bobick, I...
METAINFORMATICS
2004
Springer
15 years 5 months ago
Describing Use Cases with Activity Charts
Abstract. The Model-Driven Development (MDD) describes and maintains models of the system under development. The Unified Modeling Language (UML) supports a set of semantics and no...
Jesús Manuel Almendros-Jiménez, Luis...
BMCBI
2010
143views more  BMCBI 2010»
14 years 12 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
CVPR
2009
IEEE
16 years 6 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...