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ICML
2005
IEEE
14 years 10 months ago
Reinforcement learning with Gaussian processes
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
Yaakov Engel, Shie Mannor, Ron Meir
PAMI
2008
182views more  PAMI 2008»
13 years 9 months ago
Gaussian Process Dynamical Models for Human Motion
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
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
NIPS
2003
13 years 11 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 9 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