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ML
2010
ACM
181views Machine Learning» more  ML 2010»
13 years 3 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor
BMCBI
2010
159views more  BMCBI 2010»
13 years 5 months ago
Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
Background: Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods ha...
Alvaro J. González, Li Liao
ISBI
2004
IEEE
14 years 5 months ago
Morphological Classification of Medical Images using Nonlinear Support Vector Machines
The wavelet decomposition of a high-dimensional shape transformation posed in a mass-preserving framework is used as a morphological signature of a brain image. Population differe...
Christos Davatzikos, Dinggang Shen, Zhiqiang Lao, ...
IMSCCS
2006
IEEE
13 years 11 months ago
Parallel Multicategory Support Vector Machines (PMC-SVM) for Classifying Microcarray Data
Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of biological classification problems. However, the proc...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...
ICML
2004
IEEE
14 years 5 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...