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ICML
2004
IEEE
14 years 9 months ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
CIKM
2004
Springer
14 years 1 months ago
Hierarchical document categorization with support vector machines
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
Lijuan Cai, Thomas Hofmann
ESANN
2006
13 years 9 months ago
OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method
Abstract. We present the OnlineDoubleMaxMinOver approach to obtain the Support Vectors in two class classification problems. With its linear time complexity and linear convergence ...
Daniel Schneegaß, Thomas Martinetz, Michael ...
ISCI
2007
130views more  ISCI 2007»
13 years 8 months ago
Learning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...
PVM
2005
Springer
14 years 1 months ago
Some Improvements to a Parallel Decomposition Technique for Training Support Vector Machines
We consider a parallel decomposition technique for solving the large quadratic programs arising in training the learning methodology Support Vector Machine. At each iteration of th...
Thomas Serafini, Luca Zanni, Gaetano Zanghirati