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» Selectivity Estimation using Probabilistic Models
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ISBI
2006
IEEE
16 years 16 days ago
Two probabilistic algorithms for MEG/EEG source reconstruction
We have developed two algorithms for source imaging from MEG/EEG data. Contribution to sensor data from a source at a particular voxel is expressed as the product of a known lead ...
Johanna M. Zumer, Hagai Attias, Kensuke Sekihara, ...
ICDM
2009
IEEE
205views Data Mining» more  ICDM 2009»
15 years 6 months ago
Active Selection of Sensor Sites in Remote Sensing Applications
— In a data-mining approach, a model for estimation of Aerosol Optical Depth (AOD) from satellite observations is learned using collocated satellite and groundbased observations....
Debasish Das, Zoran Obradovic, Slobodan Vucetic
ICML
2007
IEEE
16 years 19 days ago
Kernelizing PLS, degrees of freedom, and efficient model selection
Kernelizing partial least squares (PLS), an algorithm which has been particularly popular in chemometrics, leads to kernel PLS which has several interesting properties, including ...
Mikio L. Braun, Nicole Krämer
IJCNN
2007
IEEE
15 years 6 months ago
Evaluation of Performance Measures for SVR Hyperparameter Selection
— To obtain accurate modeling results, it is of primal importance to find optimal values for the hyperparameters in the Support Vector Regression (SVR) model. In general, we sea...
Koen Smets, Brigitte Verdonk, Elsa Jordaan
SCVMA
2004
Springer
15 years 5 months ago
A Generative Model of Dense Optical Flow in Layers
We introduce a generative model of dense flow fields within a layered representation of 3-dimensional scenes. Using probabilistic inference and learning techniques (namely, varia...
Anitha Kannan, Brendan J. Frey, Nebojsa Jojic