321 search results - page 15 / 65 » Stacked Gaussian Process Learning |
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Publication
We present a new approach for activity modelling and anomaly detection based on non-parametric Gaussian Process (GP) models. Specifically, GP regression models are formulated to l...
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ECCV
2010
Springer
14 years 7 months ago
2010
Springer
We present a novel framework for the recognition of facial expressions at arbitrary poses that is based on 2D geometric features. We address the problem by first mapping the 2D loc...
IJON
2010
14 years 8 months ago
2010
We present an EM-algorithm for the problem of learning preferences with Gaussian processes in the context of multi-task learning. We validate our approach on an audiological data ...
ICML
2008
IEEE
15 years 10 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...
DSMML
2004
Springer
15 years 2 months ago
2004
Springer
Abstract. Gaussian process prior systems generally consist of noisy measurements of samples of the putatively Gaussian process of interest, where the samples serve to constrain the...