566 search results - page 22 / 114 » Nonlinear Predictive Control with a Gaussian Process Model |
JMLR
2010
14 years 8 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...
101
Voted
ICIP
2006
IEEE
16 years 3 months ago
2006
IEEE
Wavelet domain statistical modeling of images has focused on modeling the peaked heavy-tailed behavior of the marginal distribution and on modeling the dependencies between coeffi...
125
Voted
ICASSP
2011
IEEE
14 years 5 months ago
2011
IEEE
In this paper, we propose a Gaussian Process Regression (GPR) framework for concealment of corrupted motion vectors in predictive video coding of packet video systems. The problem...
92
Voted
NIPS
2003
15 years 3 months ago
2003
We introduce a class of nonstationary covariance functions for Gaussian process (GP) regression. Nonstationary covariance functions allow the model to adapt to functions whose smo...
134
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MICCAI
2009
Springer
16 years 3 months ago
2009
Springer
Patient-specific biomechanical models implemented using specialized nonlinear (i.e. taking into account material and geometric nonlinearities) finite element procedures were applie...