137 search results - page 5 / 28 » Sparse Semi-supervised Learning Using Conjugate Functions |
ICONIP
2007
13 years 9 months ago
2007
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
JMLR
2010
13 years 2 months ago
2010
Variational Bayesian (VB) methods are typically only applied to models in the conjugate-exponential family using the variational Bayesian expectation maximisation (VB EM) algorith...
IJCAI
2007
13 years 9 months ago
2007
We propose a novel variant of the conjugate gradient algorithm, Kernel Conjugate Gradient (KCG), designed to speed up learning for kernel machines with differentiable loss functio...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Real-time functional magnetic resonance imaging (rtfMRI) enables classification of brain activity during data collection thus making inference results accessible to both the subj...
CORR
2011
Springer
13 years 2 months ago
2011
Springer
— We address the sparse signal recovery problem in the context of multiple measurement vectors (MMV) when elements in each nonzero row of the solution matrix are temporally corre...