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NECO
1998
83views more  NECO 1998»
13 years 8 months ago
Properties of Support Vector Machines
Support Vector Machines (SVMs) perform pattern recognition between two point classes by nding a decision surface determined by certain points of the training set, termed Support V...
Massimiliano Pontil, Alessandro Verri
NIPS
2000
13 years 10 months ago
A Support Vector Method for Clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladi...
ENGL
2008
160views more  ENGL 2008»
13 years 8 months ago
Vector Approximation based Indexing for High-Dimensional Multimedia Databases
With the proliferation of multimedia data, there is an increasing need to support the indexing and searching of high-dimensional data. In this paper, we propose an efficient indexi...
Imane Daoudi, Saîd El Alaoui Ouatik, A. El K...
KAIS
2010
144views more  KAIS 2010»
13 years 7 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz
ICONIP
2008
13 years 10 months ago
A Vector Quantization Approach for Life-Long Learning of Categories
We present a category learning vector quantization (cLVQ) approach for incremental and life-long learning of multiple visual categories where we focus on approaching the stability-...
Stephan Kirstein, Heiko Wersing, Horst-Michael Gro...