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PAA
2008
13 years 4 months ago
A sparse Bayesian approach for joint feature selection and classifier learning
Abstract In this paper we present a new method for Joint Feature Selection and Classifier Learning (JFSCL) using a sparse Bayesian approach. These tasks are performed by optimizing...
Àgata Lapedriza, Santi Seguí, David ...
RECOMB
2003
Springer
14 years 4 months ago
Joint classifier and feature optimization for cancer diagnosis using gene expression data
Recent research has demonstrated quite convincingly that accurate cancer diagnosis can be achieved by constructing classifiers that are designed to compare the gene expression pro...
Balaji Krishnapuram, Lawrence Carin, Alexander J. ...
BMCBI
2011
12 years 8 months ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
PKDD
2010
Springer
162views Data Mining» more  PKDD 2010»
13 years 2 months ago
Expectation Propagation for Bayesian Multi-task Feature Selection
In this paper we propose a Bayesian model for multi-task feature selection. This model is based on a generalized spike and slab sparse prior distribution that enforces the selectio...
Daniel Hernández-Lobato, José Miguel...

Publication
433views
14 years 22 days ago
Optimal Feature Selection for Subspace Image Matching
Image matching has been a central research topic in computer vision over the last decades. Typical approaches for correspondence involve matching features between images. In this p...
Gemma Roig, Xavier Boix, Fernando De la Torre