79 search results - page 1 / 16 » Nonparametric Bayesian feature selection for multi-task lear... |
TSP
2008
13 years 3 months ago
2008
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
We present a nonparametric Bayesian model for multi-task learning, with a focus on feature selection in binary classification. The model jointly identifies groups of similar tas...
JMLR
2011
12 years 12 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
2008
13 years 6 months ago
2008
Almost all successful machine learning algorithms and cognitive models require powerful representations capturing the features that are relevant to a particular problem. We draw o...
JMLR
2002
13 years 4 months ago
2002
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....