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» Modelling Smooth Paths Using Gaussian Processes
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ICUMT
2009
13 years 7 months ago
Application of smoothed estimators in spectrum sensing technique based on model selection
In cognitive radio networks, secondary user (SU) does not have rights to transmit when the primary user (PU) band is occupied, that's why a sensing technique must be done. Rec...
Bassem Zayen, Aawatif Hayar, Hamza Debbabi, Hichem...
ICIP
2008
IEEE
14 years 11 months ago
On the estimation of geodesic paths on sampled manifolds under random projections
In this paper, we focus on the use of random projections as a dimensionality reduction tool for sampled manifolds in highdimensional Euclidean spaces. We show that geodesic paths ...
Mona Mahmoudi, Pierre Vandergheynst, Matteo Sorci
ICML
2008
IEEE
14 years 10 months ago
Gaussian process product models for nonparametric nonstationarity
Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covariance function, but such covaria...
Ryan Prescott Adams, Oliver Stegle
MLMI
2007
Springer
14 years 4 months ago
Gaussian Process Latent Variable Models for Human Pose Estimation
We describe a method for recovering 3D human body pose from silhouettes. Our model is based on learning a latent space using the Gaussian Process Latent Variable Model (GP-LVM) [1]...
Carl Henrik Ek, Philip H. S. Torr, Neil D. Lawrenc...
ICML
2007
IEEE
14 years 10 months ago
Discriminative Gaussian process latent variable model for classification
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
Raquel Urtasun, Trevor Darrell