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» Maximal Vector Computation in Large Data Sets
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SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
14 years 5 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic
TNN
2008
182views more  TNN 2008»
13 years 7 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
AUSAI
2005
Springer
14 years 1 months ago
Fuzzy Attribute Implications: Computing Non-redundant Bases Using Maximal Independent Sets
Abstract. This note describes a method for computation of non-redundant bases of attribute implications from data tables with fuzzy attributes. Attribute implications are formulas ...
Radim Belohlávek, Vilém Vychodil
SDM
2004
SIAM
211views Data Mining» more  SDM 2004»
13 years 9 months ago
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
ICML
2009
IEEE
14 years 2 months ago
Fast evolutionary maximum margin clustering
The maximum margin clustering approach is a recently proposed extension of the concept of support vector machines to the clustering problem. Briefly stated, it aims at finding a...
Fabian Gieseke, Tapio Pahikkala, Oliver Kramer