Results 51 to 60 of about 263,437 (264)
Wasserstein support vector machine: Support vector machines made fair
European Journal of Operational ResearchIn this paper, a novel model combining Support Vector Machines (SVM) and equity is introduced. Assuming that a group of individuals need to be protected against discrimination, we address the problem of training the classifier by jointly maximizing the classification performance (SVM margin) and equity (closeness between the distribution of the ...
Emilio Carrizosa +2 more
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Liquid biopsy‐based diagnostic evaluation of hypermethylated CpG sites for ovarian cancer diagnosis
Molecular Oncology, EarlyView.This schematic outlines the workflow from biomarker identification to duplex MethyLight assay validation for epithelial ovarian cancer diagnosis using cfDNA‐based liquid biopsy. Initial screening of hypermethylated CpG candidates (cg02957270, cg10061138 cg00480298, COL2A1) was performed in tissue using ARMS‐PCR, COBRA, qPCR and image analysis. Selected
Deepa Bisht +3 more
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Molecular Oncology, EarlyView.This review summarizes the transcription factors, repressive chromatin‐modifying complexes, and epigenetic mechanisms that control fetal hemoglobin repression. Notably, many regulators of γ‐globin silencing also function in transcriptional and epigenetic networks that drive cancer, highlighting opportunities to translate advances in hemoglobinopathy ...
Meigen Yu +3 more
wiley +1 more source
LINEX Support Vector Machine for Large-Scale Classification
IEEE Access, 2019 Traditional soft margin support vector machine usually uses hinge loss to build a classifier with the “maximum-margin” principle. However, C-SVM depends on support vectors causing the loss of data information.
Yue Ma +3 more
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Prediction of Chongqing's grain output based on support vector machine
Frontiers in Sustainable Food Systems, 2023 Scientific prediction of agricultural food production plays an essential role in stabilizing food supply. In order to improve the accuracy of grain yield prediction and reduce the error of grain yield prediction in Chongqing, this paper proposes a new ...
Jia Wang +3 more
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Molecular Oncology, EarlyView.This study identifies somatostatin receptor 4 (Sstr4) as a critical tumor suppressor against skin and head/neck cancers (HNSCC, cSCC, and BCC). The loss of Sstr4 removes a check on cell growth, causing hyperactivation of the MAPK‐ERK signaling pathway (↑).
Ali Taqvi +6 more
wiley +1 more source
Exploring Kernel Machines and Support Vector Machines: Principles, Techniques, and Future Directions
MathematicsThe kernel method is a tool that converts data to a kernel space where operation can be performed. When converted to a high-dimensional feature space by using kernel functions, the data samples are more likely to be linearly separable.
Ke-Lin Du +4 more
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Convolutional Support Vector Machine
CoRR, 2020 The support vector machine (SVM) and deep learning (e.g., convolutional neural networks (CNNs)) are the two most famous algorithms in small and big data, respectively. Nonetheless, smaller datasets may be very important, costly, and not easy to obtain in a short time.
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Tutorial on Support Vector Machines [PDF]
, 2022 Abstract The aim of this tutorial is to help students grasp the theory and applicability of support vector machines (SVMs). The contribution is an intuitive style tutorial that helped students gain insights into SVM from a unique perspective. An internet search will reveal many videos and articles on SVM, but free peer-reviewed tutorials are ...
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Semismooth support vector machines [PDF]
Mathematical Programming, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Michael C. Ferris, Todd S. Munson
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