14 search results - page 1 / 3 » Learning Gaussian Process Kernels via Hierarchical Bayes |
NIPS
2004
13 years 5 months ago
2004
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
ICDM
2009
IEEE
13 years 11 months ago
2009
IEEE
Quantile regression refers to the process of estimating the quantiles of a conditional distribution and has many important applications within econometrics and data mining, among ...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
NIPS
2008
13 years 5 months ago
2008
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
PRL
2008
13 years 4 months ago
2008
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...