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An independent dominating set D of a graph G = (V,E) is a subset of vertices such that every vertex in V \ D has at least one neighbor in D and D is an independent set, i.e. no two vertices of D are adjacent in G. Finding a minimum…

Data Structures and Algorithms · Computer Science 2010-09-08 Serge Gaspers , Mathieu Liedloff

Dependency knowledge of the form "x is independent of y once z is known" invariably obeys the four graphoid axioms, examples include probabilistic and database dependencies. Often, such knowledge can be represented efficiently with…

Artificial Intelligence · Computer Science 2013-04-10 Tom S. Verma , Judea Pearl

The assumed causal relationships depicted in a DAG are interpreted using a set of rules called D-separation rules. Although these rules can be implemented automatically using standard software, at least a basic understanding of their…

Methodology · Statistics 2025-02-20 Fernando Pires Hartwig , Timothy Feeney , Neil Davies

Network systems have become a ubiquitous modeling tool in many areas of science where nodes in a graph represent distributed processes and edges between nodes represent a form of dynamic coupling. When a network topology is already known…

Adaptation and Self-Organizing Systems · Physics 2019-05-30 Donatello Materassi , Murti V. Salapaka

The rules of d-separation provide a framework for deriving conditional independence facts from model structure. However, this theory only applies to simple directed graphical models. We introduce relational d-separation, a theory for…

Artificial Intelligence · Computer Science 2013-04-16 Marc Maier , David Jensen

We propose an alternative proof concerning necessary and sufficient conditions to split the problem of searching for d-separators and building the skeleton of a DAG into small problems for every node of a separation tree T. The proof is…

Artificial Intelligence · Computer Science 2018-07-02 Mohammad Ali Javidian , Marco Valtorta

Directed graphical models provide a useful framework for modeling causal or directional relationships for multivariate data. Prior work has largely focused on identifiability and search algorithms for directed acyclic graphical (DAG)…

Machine Learning · Statistics 2016-07-07 Gunwoong Park , Garvesh Raskutti

Chain graphs give a natural unifying point of view on Markov and Bayesian networks and enlarge the potential of graphical models for description of conditional independence structures. In the paper a direct graphical separation criterion…

Artificial Intelligence · Computer Science 2013-02-18 Milan Studeny

In this paper, we propose a novel inference method for dynamic genetic networks which makes it possible to face with a number of time measurements n much smaller than the number of genes p. The approach is based on the concept of low order…

Statistics Theory · Mathematics 2009-05-29 Sophie Lèbre

We show that the d -separation criterion constitutes a valid test for conditional independence relationships that are induced by feedback systems involving discrete variables.

Artificial Intelligence · Computer Science 2013-02-18 Judea Pearl , Rina Dechter

For a directed acyclic graph, there are two known criteria to decide whether any specific conditional independence statement is implied for all distributions factorized according to the given graph. Both criteria are based on special types…

Statistics Theory · Mathematics 2009-04-03 Giovanni M. Marchetti , Nanny Wermuth

The d-separation criterion detects the compatibility of a joint probability distribution with a directed acyclic graph through certain conditional independences. In this work, we study this problem in the context of categorical probability…

Statistics Theory · Mathematics 2023-02-21 Tobias Fritz , Andreas Klingler

A dissociation set in a graph is a set of vertices inducing a subgraph of maximum degree at most $1$. Computing the dissociation number ${\rm diss}(G)$ of a given graph $G$, defined as the order of a maximum dissociation set in $G$, is…

Combinatorics · Mathematics 2022-02-03 Felix Bock , Johannes Pardey , Lucia D. Penso , Dieter Rautenbach

Given a Bayesian network structure (directed acyclic graph), the celebrated d-separation algorithm efficiently determines whether the network structure implies a given conditional independence relation. We show that this changes drastically…

Computational Complexity · Computer Science 2024-05-14 Cheuk Ting Li

We extend the theory of d-separation to cases in which data instances are not independent and identically distributed. We show that applying the rules of d-separation directly to the structure of probabilistic models of relational data…

Artificial Intelligence · Computer Science 2014-01-07 Marc Maier , Katerina Marazopoulou , David Jensen

Causal discovery aims to recover a causal graph from data generated by it; constraint based methods do so by searching for a d-separating conditioning set of nodes in the graph via an oracle. In this paper, we provide analytic evidence that…

Machine Learning · Computer Science 2023-10-04 Itai Feigenbaum , Huan Wang , Shelby Heinecke , Juan Carlos Niebles , Weiran Yao , Caiming Xiong , Devansh Arpit

In a previous paper [Pearl and Verma, 1991] we presented an algorithm for extracting causal influences from independence information, where a causal influence was defined as the existence of a directed arc in all minimal causal models…

Artificial Intelligence · Computer Science 2013-03-25 Tom S. Verma , Judea Pearl

This paper explores the role of Directed Acyclic Graphs (DAGs) as a representation of conditional independence relationships. We show that DAGs offer polynomially sound and complete inference mechanisms for inferring conditional…

Artificial Intelligence · Computer Science 2013-04-10 Dan Geiger , Judea Pearl

A set $V$ is said to be separated by subsets $V_1,\ldots,V_k$ if, for every pair of distinct elements of $V$, there is a set $V_i$ that contains exactly one of them. Imposing structural constraints on the separating subsets is often…

Combinatorics · Mathematics 2024-08-06 Lyuben Lichev , Nicolás Sanhueza-Matamala

The minimum feedback arc set problem asks to delete a minimum number of arcs (directed edges) from a digraph (directed graph) to make it free of any directed cycles. In this work we approach this fundamental cycle-constrained optimization…

Disordered Systems and Neural Networks · Physics 2017-09-13 Yi-Zhi Xu , Hai-Jun Zhou
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