Sciweavers

3413 search results - page 4 / 683
» New Support Vector Algorithms
Sort
View
NECO
2007
107views more  NECO 2007»
13 years 8 months ago
Training a Support Vector Machine in the Primal
Most literature on Support Vector Machines (SVMs) concentrate on the dual optimization problem. In this paper, we would like to point out that the primal problem can also be solve...
Olivier Chapelle
JMLR
2006
131views more  JMLR 2006»
13 years 8 months ago
Incremental Support Vector Learning: Analysis, Implementation and Applications
Incremental Support Vector Machines (SVM) are instrumental in practical applications of online learning. This work focuses on the design and analysis of efficient incremental SVM ...
Pavel Laskov, Christian Gehl, Stefan Krüger, ...
TNN
2010
159views Management» more  TNN 2010»
13 years 3 months ago
Multiple incremental decremental learning of support vector machines
We propose a multiple incremental decremental algorithm of Support Vector Machine (SVM). Conventional single incremental decremental SVM can update the trained model efficiently w...
Masayuki Karasuyama, Ichiro Takeuchi
HICSS
2006
IEEE
97views Biometrics» more  HICSS 2006»
14 years 2 months ago
Dynamically Optimizing Parameters in Support Vector Regression: An Application of Electricity Load Forecasting
This study develops a novel model, GA-SVR, for parameters optimization in support vector regression and implements this new model in a problem forecasting maximum electrical daily...
Chin-Chia Hsu, Chih-Hung Wu, Shih-Chien Chen, Kang...
ICML
2008
IEEE
14 years 9 months ago
Stopping conditions for exact computation of leave-one-out error in support vector machines
We propose a new stopping condition for a Support Vector Machine (SVM) solver which precisely reflects the objective of the Leave-OneOut error computation. The stopping condition ...
Klaus-Robert Müller, Pavel Laskov, Vojtech Fr...