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» Gene function prediction using labeled and unlabeled data
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ICML
2010
IEEE
15 years 22 days ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum
BMCBI
2010
149views more  BMCBI 2010»
14 years 11 months ago
Identifying common prognostic factors in genomic cancer studies: A novel index for censored outcomes
Background: With the growing number of public repositories for high-throughput genomic data, it is of great interest to combine the results produced by independent research groups...
Sigrid Rouam, Thierry Moreau, Philippe Broët
BMCBI
2004
122views more  BMCBI 2004»
14 years 11 months ago
A comprehensive comparison of comparative RNA structure prediction approaches
Background: An increasing number of researchers have released novel RNA structure analysis and prediction algorithms for comparative approaches to structure prediction. Yet, indep...
Paul P. Gardner, Robert Giegerich
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
13 years 2 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
CVPR
2008
IEEE
14 years 12 months ago
Joint learning and dictionary construction for pattern recognition
We propose a joint representation and classification framework that achieves the dual goal of finding the most discriminative sparse overcomplete encoding and optimal classifier p...
Duc-Son Pham, Svetha Venkatesh