122 search results - page 2 / 25 » Nonstationary Covariance Functions for Gaussian Process Regr... |
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
ICDM
2009
IEEE
13 years 12 months ago
2009
IEEE
—Triggered by a market relevant application that involves making joint predictions of pedestrian and public transit flows in urban areas, we address the question of how to utili...
NIPS
2004
13 years 6 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...
NIPS
2001
13 years 6 months ago
2001
We present an extension to the Mixture of Experts (ME) model, where the individual experts are Gaussian Process (GP) regression models. Using an input-dependent adaptation of the ...
ICONIP
2009
13 years 3 months ago
2009
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...