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» An fMRI Activation Method Using Complex Data
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NAACL
2003
15 years 1 months ago
Active Learning for Classifying Phone Sequences from Unsupervised Phonotactic Models
This paper describes an application of active learning methods to the classification of phone strings recognized using unsupervised phonotactic models. The only training data req...
Shona Douglas
TOG
2012
582views Communications» more  TOG 2012»
13 years 2 months ago
Synthesis of detailed hand manipulations using contact sampling
Capturing human activities that involve both gross full-body motion and detailed hand manipulation of objects is challenging for standard motion capture systems. We introduce a ne...
Yuting Ye, C. Karen Liu
BIODATAMINING
2008
140views more  BIODATAMINING 2008»
14 years 12 months ago
Modeling gene-by-environment interaction in comorbid depression with alcohol use disorders via an integrated bioinformatics appr
Background: Comorbidity of Major Depressive Disorder (depression) and Alcohol Use Disorders (AUD) is well documented. Depression, AUD, and the comorbidity of depression with AUD s...
Richard C. McEachin, Benjamin J. Keller, Erika F. ...
BMCBI
2005
141views more  BMCBI 2005»
14 years 11 months ago
A method for the prediction of GPCRs coupling specificity to G-proteins using refined profile Hidden Markov Models
Background: G- Protein coupled receptors (GPCRs) comprise the largest group of eukaryotic cell surface receptors with great pharmacological interest. A broad range of native ligan...
Nikolaos G. Sgourakis, Pantelis G. Bagos, Panagiot...
COLT
2005
Springer
15 years 5 months ago
Generalization Error Bounds Using Unlabeled Data
We present two new methods for obtaining generalization error bounds in a semi-supervised setting. Both methods are based on approximating the disagreement probability of pairs of ...
Matti Kääriäinen