122 search results - page 3 / 25 » Nonstationary Covariance Functions for Gaussian Process Regr... |
NIPS
2008
13 years 9 months ago
2008
We present a sparse approximation approach for dependent output Gaussian processes (GP). Employing a latent function framework, we apply the convolution process formalism to estab...
UAI
2008
13 years 9 months ago
2008
Much recent work has concerned sparse approximations to speed up the Gaussian process regression from the unfavorable O(n3 ) scaling in computational time to O(nm2 ). Thus far, wo...
JMLR
2010
13 years 2 months ago
2010
We present a new sparse Gaussian Process (GP) model for regression. The key novel idea is to sparsify the spectral representation of the GP. This leads to a simple, practical algo...
ICDM
2010
IEEE
13 years 5 months ago
2010
IEEE
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
ICANN
2011
Springer
12 years 11 months ago
2011
Springer
This paper is concerned with estimation of learning curves for Gaussian process regression with multidimensional numerical integration. We propose an approach where the recursion e...