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CVBIA
2005
Springer
15 years 10 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
JMLR
2010
169views more  JMLR 2010»
14 years 11 months ago
Consensus-Based Distributed Support Vector Machines
This paper develops algorithms to train support vector machines when training data are distributed across different nodes, and their communication to a centralized processing unit...
Pedro A. Forero, Alfonso Cano, Georgios B. Giannak...
TNN
2010
159views Management» more  TNN 2010»
14 years 11 months ago
Multiple incremental decremental learning of support vector machines
We propose a multiple incremental decremental algorithm of Support Vector Machine (SVM). Conventional single incremental decremental SVM can update the trained model efficiently w...
Masayuki Karasuyama, Ichiro Takeuchi
ICAPR
2009
Springer
15 years 11 months ago
Relevant and Redundant Feature Analysis with Ensemble Classification
— Feature selection and ensemble classification increase system efficiency and accuracy in machine learning, data mining and biomedical informatics. This research presents an ana...
Rakkrit Duangsoithong, Terry Windeatt
WWW
2005
ACM
16 years 5 months ago
A comprehensive comparative study on term weighting schemes for text categorization with support vector machines
Term weighting scheme, which has been used to convert the documents as vectors in the term space, is a vital step in automatic text categorization. In this paper, we conducted com...
Man Lan, Chew Lim Tan, Hwee-Boon Low, Sam Yuan Sun...