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» Structural Modelling with Sparse Kernels
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ISBI
2006
IEEE
15 years 10 months ago
Nonlinear classification of EEG data for seizure detection
We address the problem of classification of EEG recordings for the detection of epileptic seizures. We assume that the EEG measurements can be described by a low dimensional manif...
Mabel Ramírez-Vélez, Richard Staba, ...
ISBI
2008
IEEE
15 years 10 months ago
Inferring brain dynamics using granger causality on fMRI data
Here we present a scalable method to compute the structure of causal links over large scale dynamical systems that achieves high efficiency in discovering actual functional connec...
Guillermo A. Cecchi, Rahul Garg, A. Ravishankar Ra...
IPPS
1999
IEEE
15 years 2 months ago
An Object-Oriented Environment for Sparse Parallel Computation on Adaptive Grids
Many numerical solutions of large scale simulation models require finer discretizations in some regions of the computational grid. When this region is not known in advance, adapti...
Salvatore Filippone, Michele Colajanni, Dario Pasc...
ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
15 years 4 months ago
Fast On-line Kernel Learning for Trees
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
PAMI
1998
85views more  PAMI 1998»
14 years 9 months ago
Shape Evolution With Structural and Topological Changes Using Blending
This paper describes a framework for the estimation of shape from sparse or incomplete range data. It uses a shape representation called blending, which allows for the geometric c...
Douglas DeCarlo, Dimitris N. Metaxas