Nonparametric Bayesian label prediction on a graph

DOI10.1016/j.csda.2017.11.008zbMath1469.62076arXiv1612.01930OpenAlexW2963405928MaRDI QIDQ1662125

Harry van Zanten, Jarno Hartog

Publication date: 17 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1612.01930

zbMATH Keywords

graphBayesian nonparametricsbinary classification

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (5)

Uncertainty Quantification in Graph-Based Classification of High Dimensional Data ⋮ Unnamed Item ⋮ Nonparametric Bayesian label prediction on a large graph using truncated Laplacian regularization ⋮ Minimax lower bounds for function estimation on graphs ⋮ Posterior consistency of semi-supervised regression on graphs

Cites Work

• Estimating a smooth function on a large graph by Bayesian Laplacian regularisation
• Nonparametric binary regression using a Gaussian process prior
• Statistical analysis of network data. Methods and models
• Learning Theory
• Bayesian Analysis of Binary and Polychotomous Response Data
• Learning Theory and Kernel Machines
• Collective dynamics of ‘small-world’ networks
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