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JMLR
2010
125views more  JMLR 2010»
13 years 2 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,...
IPMI
2001
Springer
14 years 8 months ago
Spatio-temporal Covariance Model for Medical Images Sequences: Application to Functional MRI Data
Spatial and temporal correlations which affect the signal measured in functional MRI (fMRI) are usually not considered simultaneously (i.e., as non-independent random processes) in...
Frithjof Kruggel, Habib Benali, Mélanie P&e...
CSDA
2007
108views more  CSDA 2007»
13 years 7 months ago
Diagnostics for functional regression via residual processes
We develop regression diagnostics for functional regression models which relate a functional response to predictor variables that can be multivariate vectors or random functions. ...
Jeng-Min Chiou, Hans-Georg Müller
ICASSP
2009
IEEE
14 years 2 months ago
Data-driven online variational filtering in wireless sensor networks
In this paper, a data-driven extension of the variational algorithm is proposed. Based on a few selected sensors, target tracking is performed distributively without any informati...
Hichem Snoussi, Jean-Yves Tourneret, Petar M. Djur...
NIPS
2007
13 years 9 months ago
Multi-task Gaussian Process Prediction
In this paper we investigate multi-task learning in the context of Gaussian Processes (GP). We propose a model that learns a shared covariance function on input-dependent features...
Edwin V. Bonilla, Kian Ming Chai, Christopher K. I...