Results 31 to 40 of about 725,482 (185)
BSP-Based Support Vector Regression Machine Parallel Framework [PDF]
International Journal of Networked and Distributed Computing (IJNDC), 2013 In this paper, we investigate the distributed parallel Support Vector Machine training strategy, and then propose a BSP-Based Support Vector Regression Machine Parallel Framework which can implement the most of distributed Support Vector Regression ...
Hong Zhang, Yongmei Lei
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$$\nu $$ ν -Improved nonparallel support vector machine
Scientific Reports, 2022 In this paper, a $$\nu $$ ν -improved nonparallel support vector machine ( $$\nu $$ ν -IMNPSVM) is proposed to solve binary classification problems.
Fengmin Sun, Shujun Lian
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Vector machine techniques for modeling of seismic liquefaction data
Ain Shams Engineering Journal, 2014 This article employs three soft computing techniques, Support Vector Machine (SVM); Least Square Support Vector Machine (LSSVM) and Relevance Vector Machine (RVM), for prediction of liquefaction susceptibility of soil.
Pijush Samui
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Linear Classification of data with Support Vector Machines and Generalized Support Vector Machines [PDF]
, 2016 In this paper, we study the support vector machine and introduced the notion of generalized support vector machine for classification of data. We show that the problem of generalized support vector machine is equivalent to the problem of generalized variational inequality and establish various results for the existence of solutions.
arxiv +1 more source
On Neural Quantum Support Vector Machines [PDF]
arXiv, 2023 In \cite{simon2023algorithms} we introduced four algorithms for the training of neural support vector machines (NSVMs) and demonstrated their feasibility. In this note we introduce neural quantum support vector machines, that is, NSVMs with a quantum kernel, and extend our results to this setting.
arxiv
Insensitive Stochastic Gradient Twin Support Vector Machine for Large Scale Problems [PDF]
Information Sciences, Volume 462, September 2018, Pages 114-131, 2017 Stochastic gradient descent algorithm has been successfully applied on support vector machines (called PEGASOS) for many classification problems. In this paper, stochastic gradient descent algorithm is investigated to twin support vector machines for classification.
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Advances in Mechanical Engineering, 2020 Gear pump is the key component in hydraulic drive system, and it is very significant to fault diagnosis for gear pump. The combination of sparsity empirical wavelet transform and adaptive dynamic least squares support vector machine is proposed for fault
Yan Lu, Zhiping Huang
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Gaussian Pyramid for Nonlinear Support Vector Machine
Applied Computational Intelligence and Soft Computing, 2022 Support vector machine (SVM) is one of the most efficient machine learning tools, and it is fast, simple to use, reliable, and provides accurate classification results.
Rawan Abo Zidan, George Karraz
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An Investigation on Support Vector Clustering for Big Data in Quantum Paradigm [PDF]
Quantum Information Processing volume 19, Article number: 108
(2020), 2018 The support vector clustering algorithm is a well-known clustering algorithm based on support vector machines using Gaussian or polynomial kernels. The classical support vector clustering algorithm works well in general, but its performance degrades when applied on big data.
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A fault diagnosis method of rolling bearing
Gong-kuang zidonghua, 2014 For parameter optimization of support vector machine in fault diagnosis method of rolling bearing based on support vector machine, an improved fruit fly optimization algorithm was proposed which took accuracy rate of pattern classification as taste ...
DONG Jianping, YANG Cheng, LU Xiaoli
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