Results 251 to 260 of about 114,074 (272)

A variational method for learning sparse Bayesian regression

Neurocomputing, 2006
Abstract In this paper, comparing with the Gaussian prior, the Laplacian distribution which is a sparse distribution is employed as the weight prior in the relevance vector machine (RVM) which is a method for learning sparse regression and classification.
openaire   +1 more source

Recursive Sparse Bayesian Learning

2022 China Automation Congress (CAC), 2022
Xuechun Qiao, Yasen Wang
openaire   +1 more source

Comparison of trend models for geotechnical spatial variability: Sparse Bayesian Learning vs. Gaussian Process Regression

Gondwana Research, 2023
Jianye Ching, Ikumasa Yoshida, Kok-Kwang Phoon   +2 more
exaly  

Sparse Bayesian learning for structural damage identification

Mechanical Systems and Signal Processing, 2020
Zhao Chen, Hao Sun, Hao Sun
exaly  

Multinomial Bayesian extreme learning machine for sparse and accurate classification model

Neurocomputing, 2021
Jiahua  Luo, Chi-Man Vong
exaly  

Sequential sparse Bayesian learning with applications to system identification for damage assessment and recursive reconstruction of image sequences

Computer Methods in Applied Mechanics and Engineering, 2021
Yong Huang
exaly  

An adaptive dimension-reduction method-based sparse polynomial chaos expansion via sparse Bayesian learning and Bayesian model averaging

Structural Safety, 2022
Wanxin He
exaly  

3D Probabilistic Site Characterization by Sparse Bayesian Learning

Journal of Engineering Mechanics - ASCE, 2020
Jianye Ching, Kok-Kwang Phoon
exaly  

A robust sparse Bayesian learning method for the structural damage identification by a mixture of Gaussians

Mechanical Systems and Signal Processing, 2023
Rongpeng Li, Yuzhu Xiao, Xueli Song
exaly  

Sparse Bayesian learning and the relevance vector machine

J. Mach. Learn. Res.
Summary: This paper introduces a general Bayesian framework for obtaining sparse solutions to regression and classification tasks utilizing models linear in the parameters. Although this framework is fully general, we illustrate our approach with a particular specialization that we denote the `Relevance Vector Machine' (RVM), a model of identical ...
openaire   +2 more sources