5 search results - page 1 / 1 » A majorization-minimization algorithm for (multiple) hyperpa... |
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
KDD
2012
ACM
11 years 7 months ago
2012
ACM
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
BMCBI
2010
13 years 5 months ago
2010
Background: To further understand the implementation of hyperparameters re-estimation technique in Bayesian hierarchical model, we added two more prior assumptions over the weight...