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DCC
2008
IEEE
15 years 9 months ago
Rate-Distortion Functions for Nonstationary Gaussian Autoregressive Processes
Source coding theorems and Shannon rate-distortion functions were studied for the discrete-time Wiener process by Berger and generalized to nonstationary Gaussian autoregressive p...
Robert M. Gray, Takeshi Hashimoto
NIPS
2001
14 years 11 months ago
Infinite Mixtures of Gaussian Process Experts
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 ...
Carl Edward Rasmussen, Zoubin Ghahramani
70
Voted
JMLR
2010
129views more  JMLR 2010»
14 years 4 months ago
Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
Interest in multioutput kernel methods is increasing, whether under the guise of multitask learning, multisensor networks or structured output data. From the Gaussian process pers...
Mauricio Alvarez, David Luengo, Michalis Titsias, ...
ECCV
2008
Springer
15 years 11 months ago
Online Sparse Matrix Gaussian Process Regression and Vision Applications
We present a new Gaussian Process inference algorithm, called Online Sparse Matrix Gaussian Processes (OSMGP), and demonstrate its merits with a few vision applications. The OSMGP ...
Ananth Ranganathan, Ming-Hsuan Yang
ICRA
2010
IEEE
185views Robotics» more  ICRA 2010»
14 years 7 months ago
Heteroscedastic Gaussian processes for data fusion in large scale terrain modeling
This paper presents a novel approach to data fusion for stochastic processes that model spatial data. It addresses the problem of data fusion in the context of large scale terrain ...
Shrihari Vasudevan, Fabio T. Ramos, Eric Nettleton...