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171
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SIAMAM
2008
170views more  SIAMAM 2008»
15 years 5 months ago
Absolute Stability and Complete Synchronization in a Class of Neural Fields Models
Neural fields are an interesting option for modelling macroscopic parts of the cortex involving several populations of neurons, like cortical areas. Two classes of neural field equ...
Olivier D. Faugeras, François Grimbert, Jea...
ICPR
2010
IEEE
15 years 7 months ago
A Relationship between Generalization Error and Training Samples in Kernel Regressors
A relationship between generalization error and training samples in kernel regressors is discussed in this paper. The generalization error can be decomposed into two components. On...
Akira Tanaka, Hideyuki Imai, Mineichi Kudo, Masaak...
153
Voted
UAI
2004
15 years 6 months ago
Exponential Families for Conditional Random Fields
In this paper we define conditional random fields in reproducing kernel Hilbert spaces and show connections to Gaussian Process classification. More specifically, we prove decompo...
Yasemin Altun, Alexander J. Smola, Thomas Hofmann
NIPS
2004
15 years 6 months ago
Kernel Methods for Implicit Surface Modeling
We describe methods for computing an implicit model of a hypersurface that is given only by a finite sampling. The methods work by mapping the sample points into a reproducing ker...
Bernhard Schölkopf, Joachim Giesen, Simon Spa...
134
Voted
PAMI
2008
121views more  PAMI 2008»
15 years 5 months ago
Theoretical Foundations of Spatially-Variant Mathematical Morphology Part II: Gray-Level Images
In this paper, we develop a spatially-variant (SV) mathematical morphology theory for gray-level signals and images in the euclidean space. The proposed theory preserves the geomet...
Nidhal Bouaynaya, Dan Schonfeld