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ICDM
2009
IEEE
160views Data Mining» more  ICDM 2009»
14 years 2 months ago
Fast Online Training of Ramp Loss Support Vector Machines
—A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...
Zhuang Wang, Slobodan Vucetic
JMLR
2010
159views more  JMLR 2010»
13 years 2 months ago
Semi-Supervised Learning with Max-Margin Graph Cuts
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
Branislav Kveton, Michal Valko, Ali Rahimi, Ling H...
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
WWW
2004
ACM
14 years 8 months ago
Web taxonomy integration using support vector machines
We address the problem of integrating objects from a source taxonomy into a master taxonomy. This problem is not only currently pervasive on the web, but also important to the eme...
Dell Zhang, Wee Sun Lee
KDD
2004
ACM
124views Data Mining» more  KDD 2004»
14 years 1 months ago
Incorporating prior knowledge with weighted margin support vector machines
Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...
Xiaoyun Wu, Rohini K. Srihari