Structure learning of sparse directed acyclic graphs incorporating the scale-free property

2018 ◽  
Vol 34 (2) ◽  
pp. 713-742
Author(s):  
Xiao Guo ◽  
Hai Zhang ◽  
Yao Wang ◽  
Yong Liang
Keyword(s):  
Structure Learning ◽  
Directed Acyclic Graphs ◽  
Scale Free ◽  
Acyclic Graphs

scholarly journals Chain graph reduction into Power Chain Graphs

2021 ◽  
Author(s):  
Víthor Rosa Franco ◽  
Guilherme Wang Barros ◽  
Marie Wiberg ◽  
Jacob Arie Laros
Keyword(s):  
Correlation Matrix ◽  
Graphical Model ◽  
Structure Learning ◽  
Directed Acyclic Graphs ◽  
Original Graph ◽  
Stable Algorithm ◽  
Acyclic Graphs ◽  
Learning Procedure ◽  
Correlational Data ◽  
Chain Graphs

Reduction of graphs is a class of procedures used to decrease the dimensionality of a given graph in which the properties of the reduced graph are to be induced from the properties of the larger original graph. This paper introduces both a new method for reducing chain graphs to simpler directed acyclic graphs (DAGs), that we call power chain graphs (PCG), as well as a procedure for structure learning of this new type of graph from correlational data of a Gaussian Graphical model (GGM). A definition for PCGs is given, directly followed by the reduction method. The structure learning procedure is a two-step approach: first, the correlation matrix is used to cluster the variables; and then, the averaged correlation matrix is used to discover the DAGs using the PC-stable algorithm. The results of simulations are provided to illustrate the theoretical proposal, which demonstrate initial evidence for the validity of our procedure to recover the structure of power chain graphs. The paper ends with a discussion regarding suggestions for future studies as well as some practical implications.

Weighted Independent Directed Acyclic Graphs for Resilient and Efficient Multipath Routing

2013 ◽  
Vol 3 (3) ◽  
pp. 1
Author(s):  
M. Ramakrishnan ◽  
Sowmya Swaminathan ◽  
Jayaganesan Chandresekaran
Keyword(s):  
Multipath Routing ◽  
Directed Acyclic Graphs ◽  
Acyclic Graphs

A Nettree for Simple Paths with Length Constraint and the Longest Path in Directed Acyclic Graphs

2012 ◽  
Vol 35 (10) ◽  
pp. 2194 ◽  
Author(s):  
Yan LI ◽  
Le SUN ◽  
Huai-Zhong ZHU ◽  
You-Xi WU
Keyword(s):  
Directed Acyclic Graphs ◽  
Length Constraint ◽  
Acyclic Graphs ◽  
Longest Path ◽  
Simple Paths

scholarly journals Directed acyclic graphs: An under-utilized tool for child maltreatment research

2019 ◽  
Vol 91 ◽  
pp. 78-87 ◽  
Author(s):  
Anna E. Austin ◽  
Tania A. Desrosiers ◽  
Meghan E. Shanahan
Keyword(s):  
Child Maltreatment ◽  
Directed Acyclic Graphs ◽  
Acyclic Graphs

scholarly journals On directed analogues of expander and hyperfinite graph sequences

2021 ◽  
pp. 1-14
Author(s):  
Endre Csóka ◽  
Łukasz Grabowski
Keyword(s):  
Directed Acyclic Graphs ◽  
Acyclic Graphs ◽  
Probabilistic Construction

Abstract We introduce and study analogues of expander and hyperfinite graph sequences in the context of directed acyclic graphs, which we call ‘extender’ and ‘hypershallow’ graph sequences, respectively. Our main result is a probabilistic construction of non-hypershallow graph sequences.

Efficient coding of labeled directed acyclic graphs

2003 ◽  
Vol 7 (5) ◽  
pp. 350-356 ◽  
Author(s):  
B. Steinsky
Keyword(s):  
Directed Acyclic Graphs ◽  
Efficient Coding ◽  
Acyclic Graphs

PATTERN MATCHING CODE MINIMIZATION IN REWRITING-BASED PROGRAMMING LANGUAGES

2002 ◽  
Vol 13 (06) ◽  
pp. 873-887
Author(s):  
NADIA NEDJAH ◽  
LUIZA DE MACEDO MOURELLE
Keyword(s):  
Programming Languages ◽  
Pattern Matching ◽  
Term Rewriting ◽  
Directed Acyclic Graphs ◽  
Tree Automaton ◽  
Minimal Tree ◽  
Term Rewriting Systems ◽  
Rewriting Systems ◽  
Acyclic Graphs ◽  
Space Requirements

We compile pattern matching for overlapping patterns in term rewriting systems into a minimal, tree matching automata. The use of directed acyclic graphs that shares all the isomorphic subautomata allows us to reduce space requirements. These are duplicated in the tree automaton. We design an efficient method to identify such subautomata and avoid duplicating their construction while generating the dag automaton. We compute some bounds on the size of the automata, thereby improving on previously known equivalent bounds for the tree automaton.

scholarly journals Learning Bayesian Network Classifiers: Searching in a Space of Partially Directed Acyclic Graphs

2005 ◽  
Vol 59 (3) ◽  
pp. 213-235 ◽  
Author(s):  
Silvia Acid ◽  
Luis M. de Campos ◽  
Javier G. Castellano
Keyword(s):  
Bayesian Network ◽  
Directed Acyclic Graphs ◽  
Bayesian Network Classifiers ◽  
Acyclic Graphs
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