17 search results - page 1 / 4 » Expectation Propagation for Bayesian Multi-task Feature Sele... |
CVPR
2005
IEEE
14 years 6 months ago
2005
IEEE
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
PKDD
2010
Springer
13 years 3 months ago
2010
Springer
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...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
In many real-world classification problems the input contains a large number of potentially irrelevant features. This paper proposes a new Bayesian framework for determining the r...
JMLR
2011
12 years 11 months ago
2011
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
NIPS
2007
13 years 6 months ago
2007
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...