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» Pattern vectors from the Ihara zeta function
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JMLR
2006
96views more  JMLR 2006»
13 years 5 months ago
A Hierarchy of Support Vector Machines for Pattern Detection
We introduce a computational design for pattern detection based on a tree-structured network of support vector machines (SVMs). An SVM is associated with each cell in a recursive ...
Hichem Sahbi, Donald Geman
TNN
2010
205views Management» more  TNN 2010»
13 years 1 days ago
Behavior-constrained support vector machines for fMRI data analysis
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
Danmei Chen, Sheng Li, Zoe Kourtzi, Si Wu
ICCV
2007
IEEE
14 years 7 months ago
On the Differential Geometry of 3D Flow Patterns: Generalized Helicoids and Diffusion MRI Analysis
Configurations of dense locally parallel 3D curves occur in medical imaging, computer vision and graphics. Examples include white matter fibre tracts, textures, fur and hair. We d...
Peter Savadjiev, Steven W. Zucker, Kaleem Siddiqi
ICNC
2005
Springer
13 years 10 months ago
Training Data Selection for Support Vector Machines
Abstract. In recent years, support vector machines (SVMs) have become a popular tool for pattern recognition and machine learning. Training a SVM involves solving a constrained qua...
Jigang Wang, Predrag Neskovic, Leon N. Cooper
ICANN
2007
Springer
13 years 11 months ago
Unbiased SVM Density Estimation with Application to Graphical Pattern Recognition
Abstract. Classification of structured data (i.e., data that are represented as graphs) is a topic of interest in the machine learning community. This paper presents a different,...
Edmondo Trentin, Ernesto Di Iorio