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KDD
2000
ACM
133views Data Mining» more  KDD 2000»
15 years 6 months ago
Data selection for support vector machine classifiers
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
Glenn Fung, Olvi L. Mangasarian
SDM
2004
SIAM
211views Data Mining» more  SDM 2004»
15 years 3 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...
KDD
2001
ACM
145views Data Mining» more  KDD 2001»
16 years 2 months ago
Proximal support vector machine classifiers
Given a dataset, each element of which labeled by one of k labels, we construct by a very fast algorithm, a k-category proximal support vector machine (PSVM) classifier. Proximal s...
Glenn Fung, Olvi L. Mangasarian
106
Voted
EVOW
2007
Springer
15 years 6 months ago
Classification of Cell Fates with Support Vector Machine Learning
In human mesenchymal stem cells the envelope surrounding the nucleus, as visualized by the nuclear lamina, has a round and flat shape. The lamina structure is considerably deformed...
Ofer M. Shir, Vered Raz, Roeland W. Dirks, Thomas ...
ICIP
2009
IEEE
15 years 3 days ago
Efficient reduction of support vectors in kernel-based methods
Kernel-based methods, e.g., support vector machine (SVM), produce high classification performances. However, the computation becomes time-consuming as the number of the vectors su...
Takumi Kobayashi, Nobuyuki Otsu