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ECML
2006
Springer
13 years 11 months ago
Bayesian Active Learning for Sensitivity Analysis
Abstract. Designs of micro electro-mechanical devices need to be robust against fluctuations in mass production. Computer experiments with tens of parameters are used to explore th...
Tobias Pfingsten
CSDA
2008
77views more  CSDA 2008»
13 years 7 months ago
Maximizing equity market sector predictability in a Bayesian time-varying parameter model
A large body of evidence has emerged in recent studies confirming that macroeconomic factors play an important role in determining investor risk premia and the ultimate path of eq...
Lorne D. Johnson, Georgios Sakoulis
JMLR
2008
209views more  JMLR 2008»
13 years 7 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
DSP
2007
13 years 7 months ago
Variational and stochastic inference for Bayesian source separation
We tackle the general linear instantaneous model (possibly underdetermined and noisy) where we model the source prior with a Student t distribution. The conjugate-exponential char...
Ali Taylan Cemgil, Cédric Févotte, S...
ISBI
2002
IEEE
14 years 8 months ago
Robust estimation of the hemodynamic response function in asynchronous multitasks multisessions event-related fMRI paradigms
Hemodynamic Response Function (HRF) estimation in noisy functional Magnetic Resonance Imaging (fMRI) is essential for a better understanding of cerebral activations. Previous work...
Guillaume Marrelec, Habib Benali, Jérô...