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JMLR
2010
125views more  JMLR 2010»
12 years 11 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,...
JMLR
2010
147views more  JMLR 2010»
12 years 11 months ago
Gaussian Processes for Machine Learning (GPML) Toolbox
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library ...
Carl Edward Rasmussen, Hannes Nickisch
ICRA
2010
IEEE
145views Robotics» more  ICRA 2010»
13 years 2 months ago
Modeling and decision making in spatio-temporal processes for environmental surveillance
Abstract— The need for efficient monitoring of spatiotemporal dynamics in large environmental surveillance applications motivates the use of robotic sensors to achieve sufficie...
Amarjeet Singh 0003, Fabio Ramos, Hugh D. Whyte, W...
NIPS
2003
13 years 5 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
NIPS
2004
13 years 5 months ago
Dependent Gaussian Processes
Gaussian processes are usually parameterised in terms of their covariance functions. However, this makes it difficult to deal with multiple outputs, because ensuring that the cova...
Phillip Boyle, Marcus R. Frean