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KDD
2000
ACM
133views Data Mining» more  KDD 2000»
14 years 2 days 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
NIPS
1998
13 years 9 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
NN
2000
Springer
161views Neural Networks» more  NN 2000»
13 years 8 months ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys
ISM
2005
IEEE
138views Multimedia» more  ISM 2005»
14 years 2 months ago
Investigation of Combining SVM and Decision Tree for Emotion Classification
This paper discusses the use of a combination of support vector machine and decision tree learning for recognizing four emotions in speech, which are Neutral, Angry, Lombard, and ...
Thao Nguyen, Mingkun Li, Iris Bass, Ishwar K. Seth...
TSP
2008
180views more  TSP 2008»
13 years 8 months ago
Support Vector Machine Training for Improved Hidden Markov Modeling
We present a discriminative training algorithm, that uses support vector machines (SVMs), to improve the classification of discrete and continuous output probability hidden Markov ...
Alba Sloin, David Burshtein