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» Predicting Time Series with Support Vector Machines
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BMCBI
2010
159views more  BMCBI 2010»
13 years 7 months ago
Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
Background: Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods ha...
Alvaro J. González, Li Liao
NIPS
1998
13 years 8 months ago
Using Analytic QP and Sparseness to Speed Training of Support Vector Machines
Training a Support Vector Machine (SVM) requires the solution of a very large quadratic programming (QP) problem. This paper proposes an algorithm for training SVMs: Sequential Mi...
John C. Platt
NIPS
2003
13 years 8 months ago
Dynamical Modeling with Kernels for Nonlinear Time Series Prediction
We consider the question of predicting nonlinear time series. Kernel Dynamical Modeling (KDM), a new method based on kernels, is proposed as an extension to linear dynamical model...
Liva Ralaivola, Florence d'Alché-Buc
WINE
2005
Springer
268views Economy» more  WINE 2005»
14 years 27 days ago
Mining Stock Market Tendency Using GA-Based Support Vector Machines
In this study, a hybrid intelligent data mining methodology, genetic algorithm based support vector machine (GASVM) model, is proposed to explore stock market tendency. In this hyb...
Lean Yu, Shouyang Wang, Kin Keung Lai
ICASSP
2008
IEEE
14 years 1 months ago
Hybrid feature selection for gesture recognition using support vector machines
This paper presents an approach for a multi-cue based two-dimensional gesture recognition that combines two different forms of cues, namely shape cues and motion cues, in a suppor...
Yu Yuan, Kenneth Barner