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CGF
2005
252views more  CGF 2005»
13 years 8 months ago
Support Vector Machines for 3D Shape Processing
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Florian Steinke, Bernhard Schölkopf, Volker B...
ACTAC
2006
126views more  ACTAC 2006»
13 years 8 months ago
Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms
In this paper we introduce a statistical Named Entity recognizer (NER) system for the Hungarian language. We examined three methods for identifying and disambiguating proper nouns...
Richárd Farkas, György Szarvas, Andr&a...
ECTEL
2007
Springer
14 years 2 months ago
Profiled Search Methods for e-Learning Systems
Most currently used e-Learning Systems do not often offer search functionality. Even if methods are provided to search for Learning Objects (LOs), they don’t usually utilize info...
Tomasz Orzechowski, Sebastian Ernst, Andrzej Dziec...
ICML
2007
IEEE
14 years 8 months ago
A kernel path algorithm for support vector machines
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
CIBCB
2006
IEEE
14 years 2 months ago
Machine Learning in Basecalling Decoding Trace Peak Behaviour
— DNA sequence basecalling is commonly regarded as a solved problem, despite significant error rates being reflected in inaccuracies in databases and genome annotations. These er...
David Thornley, Stavros Petridis