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AUTOMATICA
2010
96views more  AUTOMATICA 2010»
15 years 6 months ago
On resampling and uncertainty estimation in Linear System Identification
Linear System Identification yields a nominal model parameter, which minimizes a specific criterion based on the single inputoutput data set. Here we investigate the utility of va...
Simone Garatti, Robert R. Bitmead
ICCV
2001
IEEE
16 years 8 months ago
Markov Face Models
The spatial distribution of gray level intensities in an image can be naturally modeled using Markov Random Field (MRF) models. We develop and investigate the performance of face ...
Sarat C. Dass, Anil K. Jain
MA
2010
Springer
172views Communications» more  MA 2010»
15 years 4 months ago
On Monte Carlo methods for Bayesian multivariate regression models with heavy-tailed errors
We consider Bayesian analysis of data from multivariate linear regression models whose errors have a distribution that is a scale mixture of normals. Such models are used to analy...
Vivekananda Roy, James P. Hobert
ACL
2007
15 years 7 months ago
Randomised Language Modelling for Statistical Machine Translation
A Bloom filter (BF) is a randomised data structure for set membership queries. Its space requirements are significantly below lossless information-theoretic lower bounds but it ...
David Talbot, Miles Osborne
FSS
2008
87views more  FSS 2008»
15 years 6 months ago
Representing parametric probabilistic models tainted with imprecision
Numerical possibility theory, belief function have been suggested as useful tools to represent imprecise, vague or incomplete information. They are particularly appropriate in unc...
Cédric Baudrit, Didier Dubois, Nathalie Per...