Gaussian conditional random fields extended for directed graphs

DOI10.1007/S10994-016-5611-7zbMath1460.62084OpenAlexW2598364170MaRDI QIDQ1698833

Fang Zhou, Jesse Glass, Zoran Obradovic, Tijana Vujicic

Publication date: 16 February 2018

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-016-5611-7

zbMATH Keywords

asymmetric structurestructured regressiondirected Gaussian conditional random fieldsGaussian conditional random fields

Mathematics Subject Classification ID

Random fields (60G60) Random fields; image analysis (62M40) Estimation in multivariate analysis (62H12) Applications of graph theory (05C90) General nonlinear regression (62J02) Probabilistic graphical models (62H22)

Related Items (1)

Another estimation of Laplacian spectrum of the Kronecker product of graphs

Uses Software

• alr3

Cites Work

• Unnamed Item
• EXPLOITING SYNTACTIC, SEMANTIC, AND LEXICAL REGULARITIES IN LANGUAGE MODELING VIA DIRECTED MARKOV RANDOM FIELDS
• Applied Linear Regression
• IV.—On Least Squares and Linear Combination of Observations

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