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» Modelling Smooth Paths Using Gaussian Processes
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JMLR
2010
141views more  JMLR 2010»
13 years 5 months ago
Hierarchical Gaussian Process Regression
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Sunho Park, Seungjin Choi
ECCV
2010
Springer
13 years 9 months ago
Coupled Gaussian Process Regression for Pose-Invariant Facial Expression Recognition
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...
Ognjen Rudovic, Ioannis Patras, Maja Pantic
ICML
2007
IEEE
14 years 11 months ago
Most likely heteroscedastic Gaussian process regression
This paper presents a novel Gaussian process (GP) approach to regression with inputdependent noise rates. We follow Goldberg et al.'s approach and model the noise variance us...
Kristian Kersting, Christian Plagemann, Patrick Pf...
ICCV
2007
IEEE
15 years 26 days ago
Active Learning with Gaussian Processes for Object Categorization
Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate of uncertainty. Gauss...
Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Tr...
IGARSS
2009
13 years 8 months ago
Spatially Adaptive Classification of Hyperspectral Data with Gaussian Processes
Automated classification of land cover types based on hyperspectral imagery often involves a large geographical area, but class labels are available for only small portions of the...
Goo Jun, Joydeep Ghosh