Generalization performance of Lagrangian support vector machine based on Markov sampling
type: Item
instance of: scholarly article
title: Generalization performance of Lagrangian support vector machine based on Markov sampling
zbMATH Open document ID: 1465.62144
author: JingJing Zeng
author: Yuze Duan
author: Desheng Wang
author: Bin Zou
author: Yue Yin
author: Jie Xu
published in: Journal of Statistical Planning and Inference
publication date: 2021-05-07T00:00:00Z
Mathematics Subject Classification ID: 62M05
Mathematics Subject Classification ID: 62D05
zbMATH DE Number: 7346475
zbMATH Keywords: Lagrangian support vector machines (LSVM)
zbMATH Keywords: Markov sampling
zbMATH Keywords: strongly mixing
zbMATH Keywords: i.i.d.
zbMATH Keywords: generalization bound
MaRDI profile type: Publication
full work available at URL: j.jspi.2020.09.001
OpenAlex ID: W3108828978
cites work: Theory of Reproducing Kernels
cites work: Q3093220
cites work: On the mathematical foundations of learning
cites work: Regularization networks and support vector machines
cites work: 10.1162/15324430152748218
cites work: Uniform ergodicity and strong mixing
cites work: Consistency of Support Vector Machines and Other Regularized Kernel Classifiers
cites work: Support Vector Machines
cites work: Q4261789
cites work: Learning and generalisation. With applications to neural networks.
cites work: Learning rates of least-square regularized regression
cites work: Learning rates of regularized regression for exponentially strongly mixing sequence
cites work: Online Regularized Classification Algorithms
cites work: Rates of convergence for empirical processes of stationary mixing sequences
cites work: 10.1162/153244302760200713
cites work: Statistical behavior and consistency of classification methods based on convex risk minimization.
cites work: The generalization performance of ERM algorithm with strongly mixing observations
DOI: 10.1016/J.JSPI.2020.09.001
description: scientific article; zbMATH DE number 7346475