High-Dimensional Sparse Graph Estimation by Integrating DTW-D Into Bayesian Gaussian Graphical Models

High-Dimensional Sparse Graph Estimation by Integrating DTW-D Into Bayesian Gaussian Graphical Models

Graphical models provide an effective way to reveal complicated associations in data and especially to learn the structures among large numbers of variables with respect to few observations in a high-dimensional space. In this paper, a novel graphical algorithm that integrates the dynamic time warpi...

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Bibliographic Details
Main Authors: Ying Li, Xiaojun Xu, Jianbo Li
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Bayesian model selection
birth-death process
dynamic time warping
graphical structure learning
G-Wishart
Markov chain Monte Carlo
Online Access:https://ieeexplore.ieee.org/document/8396215/

Internet

https://ieeexplore.ieee.org/document/8396215/

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