Adaboost-based ensemble of polynomial chaos expansion with adaptive sampling
type: Item
instance of: scholarly article
title: Adaboost-based ensemble of polynomial chaos expansion with adaptive sampling
author: Yicheng Zhou
author: Kai Cheng
author: Zhenzhou Lü
published in: Computer Methods in Applied Mechanics and Engineering
publication date: 2021-12-13T00:00:00Z
Mathematics Subject Classification ID: 65N30
Mathematics Subject Classification ID: 65N99
zbMATH DE Number: 7442800
zbMATH Keywords: uncertainty quantification
zbMATH Keywords: polynomial chaos expansion
zbMATH Keywords: adaptive sampling
zbMATH Keywords: ensemble learning
MaRDI profile type: Publication
full work available at URL: j.cma.2021.114238
OpenAlex ID: W3210851548
cites work: Physical Systems with Random Uncertainties: Chaos Representations with Arbitrary Probability Measure
cites work: The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
cites work: A new non-intrusive polynomial chaos using higher order sensitivities
cites work: Some greedy algorithms for sparse polynomial chaos expansions
cites work: Adaptive sparse polynomial chaos expansion based on least angle regression
cites work: Compressive sampling of polynomial chaos expansions: convergence analysis and sampling strategies
cites work: Enhancing \(\ell_1\)-minimization estimates of polynomial chaos expansions using basis selection
cites work: Finding maximin Latin hypercube designs by iterated local search heuristics
cites work: Metamodels for computer-based engineering design: Survey and recommendations
cites work: Uniformly distributed sequences with an additional uniform property
cites work: Least squares polynomial chaos expansion: a review of sampling strategies
cites work: Sparse polynomial chaos expansions via compressed sensing and D-optimal design
cites work: Nonadaptive quasi-optimal points selection for least squares linear regression
cites work: Adaptive weighted least-squares polynomial chaos expansion with basis adaptivity and sequential adaptive sampling
cites work: An efficient and robust adaptive sampling method for polynomial chaos expansion in sparse Bayesian learning framework
cites work: Global optimization method using adaptive and parallel ensemble of surrogates for engineering design optimization
cites work: Bagging predictors
cites work: SAMBA: sparse approximation of moment-based arbitrary polynomial chaos
cites work: Sparse Approximate Solutions to Linear Systems
cites work: Subspace Pursuit for Compressive Sensing Signal Reconstruction
cites work: Analysis of Orthogonal Matching Pursuit Using the Restricted Isometry Property
cites work: Least angle regression. (With discussion)
cites work: Compressed sensing
cites work: Model selection for small sample regression
cites work: Q3959963
cites work: A decision-theoretic generalization of on-line learning and an application to boosting
cites work: Experiments with AdaBoost.RT, an Improved Boosting Scheme for Regression
cites work: Ensembling neural networks: Many could be better than all
cites work: A sweepline algorithm for Voronoi diagrams
cites work: The quickhull algorithm for convex hulls
cites work: Q5172384
cites work: A non-adapted sparse approximation of PDEs with stochastic inputs
cites work: Convergence study of the truncated Karhunen-Loève expansion for simulation of stochastic processes
cites work: EXTENDING CLASSICAL SURROGATE MODELING TO HIGH DIMENSIONS THROUGH SUPERVISED DIMENSIONALITY REDUCTION: A DATA-DRIVEN APPROACH
DOI: 10.1016/J.CMA.2021.114238
description: scientific article; zbMATH DE number 7442800