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ICML
2008
IEEE
14 years 9 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
NIPS
2008
13 years 10 months ago
Multi-task Gaussian Process Learning of Robot Inverse Dynamics
The inverse dynamics problem for a robotic manipulator is to compute the torques needed at the joints to drive it along a given trajectory; it is beneficial to be able to learn th...
Kian Ming Adam Chai, Christopher K. I. Williams, S...
NIPS
2003
13 years 10 months ago
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
Neil D. Lawrence
TIT
2002
69views more  TIT 2002»
13 years 8 months ago
On the second derivative of a Gaussian process envelope
In this paper we explore some dynamic characteristics of the envelope of a bandpass Gaussian process, which are of interest in wireless fading channels. Specifically, we show that ...
Ali Abdi
JMLR
2010
125views more  JMLR 2010»
13 years 3 months ago
Regret Bounds for Gaussian Process Bandit Problems
Bandit algorithms are concerned with trading exploration with exploitation where a number of options are available but we can only learn their quality by experimenting with them. ...
Steffen Grünewälder, Jean-Yves Audibert,...