73 search results - page 5 / 15 » Sparse Bayesian Learning Based on an Efficient Subset Select... |
JMLR
2002
13 years 7 months ago
2002
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
ICASSP
2008
IEEE
14 years 2 months ago
2008
IEEE
We consider the problem of learning multiscale graphical models. Given a collection of variables along with covariance specifications for these variables, we introduce hidden var...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
We present a Bayesian search algorithm for learning the structure of latent variable models of continuous variables. We stress the importance of applying search operators designed...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of t...
JMLR
2002
13 years 7 months ago
2002
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...