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» Modelling Smooth Paths Using Gaussian Processes
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ESSMAC
2003
Springer
14 years 1 months ago
Nonlinear Predictive Control with a Gaussian Process Model
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
Jus Kocijan, Roderick Murray-Smith
ACCV
2007
Springer
14 years 2 months ago
Image Segmentation Using Iterated Graph Cuts Based on Multi-scale Smoothing
We present a novel approach to image segmentation using iterated Graph Cuts based on multi-scale smoothing. We compute the prior probability obtained by the likelihood from a color...
Tomoyuki Nagahashi, Hironobu Fujiyoshi, Takeo Kana...
CORR
2010
Springer
174views Education» more  CORR 2010»
13 years 8 months ago
Gaussian Process Bandits for Tree Search
We motivate and analyse a new Tree Search algorithm, based on recent advances in the use of Gaussian Processes for bandit problems. We assume that the function to maximise on the ...
Louis Dorard, John Shawe-Taylor
ESANN
2006
13 years 10 months ago
Stochastic Processes for Canonical Correlation Analysis
We consider two stochastic process methods for performing canonical correlation analysis (CCA). The first uses a Gaussian Process formulation of regression in which we use the cur...
Colin Fyfe, Gayle Leen
IROS
2008
IEEE
123views Robotics» more  IROS 2008»
14 years 3 months ago
Learning predictive terrain models for legged robot locomotion
— Legged robots require accurate models of their environment in order to plan and execute paths. We present a probabilistic technique based on Gaussian processes that allows terr...
Christian Plagemann, Sebastian Mischke, Sam Prenti...