Smooth twin support vector machines via unconstrained convex minimization

DOI10.2298/FIL1708195TOpenAlexW1952030594MaRDI QIDQ5156282

No author found.

Publication date: 15 October 2021

Published in: Filomat (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2298/fil1708195t

zbMATH Keywords

smoothing techniquesmachine learningconvex minimizationtwin support vector machineLagrangian support vector machines

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Convex programming (90C25) Learning and adaptive systems in artificial intelligence (68T05) Quadratic programming (90C20)

Related Items (2)

General twin support vector machine with pinball loss function ⋮ A method of dimensionality reduction by selection of components in principal component analysis for text classification

Uses Software

• UCI-ml
• LIBSVM
• SSVM
• RSVM

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Large-scale linear nonparallel support vector machine solver
• An efficient weighted Lagrangian twin support vector machine for imbalanced data classification
• Nonlinear complementarity as unconstrained and constrained minimization
• TSVR: an efficient twin support vector machine for regression
• Support-vector networks
• Fuzzy Twin Support Vector Machines for Pattern Classification
• 10.1162/15324430152748218
• A finite newton method for classification
• Linear programming twin support vector regression
• SSVM: A smooth support vector machine for classification

This page was built for publication: Smooth twin support vector machines via unconstrained convex minimization