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» Support Vector Machines for 3D Shape Processing
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CICLING
2006
Springer
15 years 8 months ago
Verb Sense Disambiguation Using Support Vector Machines: Impact of WordNet-Extracted Features
The disambiguation of verbs is usually considered to be more difficult with respect to other part-of-speech categories. This is due both to the high polysemy of verbs compared with...
Davide Buscaldi, Paolo Rosso, Ferran Pla, Encarna ...
CIBCB
2006
IEEE
15 years 11 months ago
Visualization of Support Vector Machines with Unsupervised Learning
– The visualization of support vector machines in realistic settings is a difficult problem due to the high dimensionality of the typical datasets involved. However, such visuali...
Lutz Hamel
ICML
2005
IEEE
16 years 5 months ago
Object correspondence as a machine learning problem
We propose machine learning methods for the estimation of deformation fields that transform two given objects into each other, thereby establishing a dense point to point correspo...
Bernhard Schölkopf, Florian Steinke, Volker B...
JMLR
2008
114views more  JMLR 2008»
15 years 4 months ago
Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
148
Voted
ML
2002
ACM
220views Machine Learning» more  ML 2002»
15 years 4 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich