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ICCS
2003
Springer
15 years 3 months ago
A Method of Hidden Markov Model Optimization for Use with Geophysical Data Sets
Geophysics research has been faced with a growing need for automated techniques with which to process large quantities of data. A successful tool must meet a number of requirements...
Robert A. Granat
ICONIP
2009
14 years 7 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
CSDA
2011
14 years 4 months ago
Hierarchical multilinear models for multiway data
Reduced-rank decompositions provide descriptions of the variation among the elements of a matrix or array. In such decompositions, the elements of an array are expressed as produc...
Peter D. Hoff
ICASSP
2011
IEEE
14 years 1 months ago
Data driven model based least squares image reconstruction for radio astronomy
Image reconstruction problems in radio astronomy and other fields like biomedical imaging are often ill-posed and some form of regularization is required. This imposes user speci...
Stefan J. Wijnholds, Alle-Jan van der Veen
CVPR
2012
IEEE
13 years 8 days ago
Multitarget data association with higher-order motion models
We present an iterative approximate solution to the multidimensional assignment problem under general cost functions. The method maintains a feasible solution at every step, and i...
Robert T. Collins