High order Parzen windows and randomized sampling

DOI10.1007/s10444-008-9073-8zbMath1183.68514OpenAlexW2053225779MaRDI QIDQ1047130

Ding-Xuan Zhou, Xiang-Jun Zhou

Publication date: 4 January 2010

Published in: Advances in Computational Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10444-008-9073-8

zbMATH Keywords

learning theorymultivariate approximation

Mathematics Subject Classification ID

General nonlinear regression (62J02) Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Learning theory viewpoint of approximation by positive linear operators ⋮ Semi-supervised learning with the help of Parzen windows ⋮ Quantile regression with \(\ell_1\)-regularization and Gaussian kernels ⋮ Parzen windows for multi-class classification ⋮ Optimal convergence rates of high order Parzen windows with unbounded sampling ⋮ Random sampling in shift invariant spaces ⋮ Least-square regularized regression with non-iid sampling ⋮ Concentration estimates for the moving least-square method in learning theory ⋮ Statistical analysis of the moving least-squares method with unbounded sampling

Uses Software

• KernSmooth

Cites Work

• Model selection for regularized least-squares algorithm in learning theory
• Risk bounds for random regression graphs
• Learning and approximation by Gaussians on Riemannian manifolds
• Optimal rates of convergence for nonparametric estimators
• Exact mean integrated squared error
• A practical guide to splines
• Approximation with scaled shift-invariant spaces by means of quasi-projection operators
• Optimum bounds for the distributions of martingales in Banach spaces
• Regularization networks and support vector machines
• Learning rates of least-square regularized regression
• Shannon sampling. II: Connections to learning theory
• Learning theory estimates via integral operators and their approximations
• Nonuniform Sampling and Reconstruction in Shift-Invariant Spaces
• ONLINE LEARNING WITH MARKOV SAMPLING
• Ten Lectures on Wavelets
• Approximation from Shift-Invariant Spaces by Integral Operators
• Shannon sampling and function reconstruction from point values
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
• On Estimation of a Probability Density Function and Mode
• Combinatorial methods in density estimation
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item