Articles with "twin support" as a keyword



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A safe screening rule for accelerating weighted twin support vector machine

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Published in 2019 at "Soft Computing"

DOI: 10.1007/s00500-018-3397-1

Abstract: Weighted twin support vector machine with local information (WLTSVM) is a novel algorithm for binary classification problems. It can exploit as much underlying correlation information as possible. Unfortunately, it remains challenging to apply WLTSVM into… read more here.

Keywords: weighted twin; ssr wltsvm; wltsvm; screening rule ... See more keywords
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Asymmetric ν-twin support vector regression

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Published in 2017 at "Neural Computing and Applications"

DOI: 10.1007/s00521-017-2966-z

Abstract: Twin support vector regression (TSVR) aims at finding ????-insensitive up- and down-bound functions for the training points by solving a pair of smaller-sized quadratic programming problems (QPPs) rather than a single large one as in… read more here.

Keywords: twin support; vector regression; regression; support vector ... See more keywords
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Fixed-point twin support vector machine

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Published in 2017 at "Cluster Computing"

DOI: 10.1007/s10586-017-1572-2

Abstract: Twin support vector machine and many of its variants proposed recently generate two optimal separating hyperplanes by solving two dual constrained quadratic programming problems (QPPs) independently. However, each dual QPP involves a set of dual… read more here.

Keywords: twin support; vector machine; support vector;
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Combined ripplet and total variation image denoising methods using twin support vector machines

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Published in 2017 at "Multimedia Tools and Applications"

DOI: 10.1007/s11042-017-4618-9

Abstract: The main goals of denoising are to improve the signal-to-noise-ratio (SNR) and to preserve the informative features such as edges and textures. Aiming at reducing Gibbs-type artifacts, several researchers have combined wavelet-like transforms such as… read more here.

Keywords: image; variation; using twin; total variation ... See more keywords
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Domain Adaptation with Twin Support Vector Machines

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Published in 2017 at "Neural Processing Letters"

DOI: 10.1007/s11063-017-9775-3

Abstract: Supervised learning models assume that the training and test data are drawn from the same underlying distribution. These algorithms become ineffective when such assumptions are violated. Therefore, domain adaptation methods were proposed to handle data… read more here.

Keywords: vector machines; twin support; domain adaptation; support vector ... See more keywords
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Twin support vector machines: A survey

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Published in 2018 at "Neurocomputing"

DOI: 10.1016/j.neucom.2018.01.093

Abstract: Abstract Twin support vector machines (TWSVM) is a new machine learning method based on the theory of Support Vector Machine (SVM). Unlike SVM, TWSVM would generate two non-parallel planes, such that each plane is closer… read more here.

Keywords: twsvm; support vector; vector machines; twin support ... See more keywords
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Ν-projection Twin Support Vector Machine for Pattern Classification

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Published in 2020 at "Neurocomputing"

DOI: 10.1016/j.neucom.2019.09.069

Abstract: Abstract In this paper, we improve the projection twin support vector machine (PTSVM) to a novel nonparallel classifier, termed as ν-PTSVM. Specifically, our ν-PTSVM aims to seek an optimal projection for each class such that,… read more here.

Keywords: support vector; class; projection; twin support ... See more keywords
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A novel prediction method for favorable reservoir of oil field based on grey wolf optimizer and twin support vector machine

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Published in 2020 at "Journal of Petroleum Science and Engineering"

DOI: 10.1016/j.petrol.2020.106952

Abstract: Abstract Most of the domestic oil fields are in the middle or late stage of exploration and development, and there are fewer and fewer oil fields that can be easily discovered. Proved reserves are dominated… read more here.

Keywords: twin support; prediction; vector machine; support vector ... See more keywords
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Twin support vector machine-based hyperspectral unmixing and its uncertainty analysis

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Published in 2020 at "Journal of Applied Remote Sensing"

DOI: 10.1117/1.jrs.14.046504

Abstract: Abstract. In consideration of within-class endmember variability, it is realistic to use multiple endmembers to model a pure class. We propose an advanced multi-endmember unmixing algorithm based on twin support vector machines (UTSVM), which derives… read more here.

Keywords: abundance; unmixing uncertainty; uncertainty; support vector ... See more keywords
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Variational mode decomposition combined fuzzy—Twin support vector machine model with deep learning for solar photovoltaic power forecasting

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Published in 2022 at "PLoS ONE"

DOI: 10.1371/journal.pone.0273632

Abstract: A novel Variational Mode Decomposition (VMD) combined Fuzzy-Twin Support Vector Machine Model with deep learning mechanism is devised in this research study to forecast the solar Photovoltaic (PV) output power in day ahead basis. The… read more here.

Keywords: vector machine; support vector; power; model ... See more keywords