98 search results - page 1 / 20 » Gaussian Process Learning from Order Relationships Using Exp... |
ICPR
2010
IEEE
13 years 9 months ago
2010
IEEE
A method for Gaussian process learning of a scalar function from a set of pair-wise order relationships is presented. Expectation propagation is used to obtain an approximation to...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covariance function, but such covaria...
WEBI
2010
Springer
13 years 2 months ago
2010
Springer
In this paper, we propose a Relation Expansion framework, which uses a few seed sentences marked up with two entities to expand a set of sentences containing target relations. Duri...
PAMI
2006
13 years 4 months ago
2006
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
ISNN
2010
Springer
13 years 3 months ago
2010
Springer
Abstract. This paper proposes a new learning method for process neural networks (PNNs) based on the Gaussian mixture functions and particle swarm optimization (PSO), called PSO-LM....