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Let $G$ be a simple graph with vertex set $V(G)$. A set $S\subseteq V(G)$ is independent if no two vertices from $S$ are adjacent. For $X\subseteq V(G)$, the difference of $X$ is $d(X) = |X|-|N(X)|$ and an independent set $A$ is critical if…

Combinatorics · Mathematics 2015-09-18 Taylor Short

In this article, we propose a new hypothesis testing method for directed acyclic graph (DAG). While there is a rich class of DAG estimation methods, there is a relative paucity of DAG inference solutions. Moreover, the existing methods…

Machine Learning · Statistics 2023-05-25 Chengchun Shi , Yunzhe Zhou , Lexin Li

We introduce a technique called graph fission which takes in a graph which potentially contains only one observation per node (whose distribution lies in a known class) and produces two (or more) independent graphs with the same node/edge…

Methodology · Statistics 2024-01-30 James Leiner , Aaditya Ramdas

We develop the theory linking 'E-separation' in directed mixed graphs (DMGs) with conditional independence relations among coordinate processes in stochastic differential equations (SDEs), where causal relationships are determined by "which…

Machine Learning · Computer Science 2025-03-14 Georg Manten , Cecilia Casolo , Søren Wengel Mogensen , Niki Kilbertus

Graph entity dependencies (GEDs) are novel graph constraints, unifying keys and functional dependencies, for property graphs. They have been found useful in many real-world data quality and data management tasks, including fact checking on…

Databases · Computer Science 2023-07-04 Dehua Liu , Selasi Kwashie , Yidi Zhang , Guangtong Zhou , Michael Bewong , Xiaoying Wu , Xi Guo , Keqing He , Zaiwen Feng

In the literature, several identification problems in graphs have been studied, of which, the most widely studied are the ones based on dominating sets as a tool of identification. Hereby, the objective is to separate any two vertices of a…

Combinatorics · Mathematics 2026-01-29 Dipayan Chakraborty , Annegret K. Wagler

We present two new combinatorial tools for the design of parameterized algorithms. The first is a simple linear time randomized algorithm that given as input a $d$-degenerate graph $G$ and an integer $k$, outputs an independent set $Y$,…

Data Structures and Algorithms · Computer Science 2017-05-04 Daniel Lokshtanov , Fahad Panolan , Saket Saurabh , Roohani Sharma , Meirav Zehavi

We present a graphical approach to deriving inequality constraints for directed acyclic graph (DAG) models, where some variables are unobserved. In particular we show that the observed distribution of a discrete model is always restricted…

Statistics Theory · Mathematics 2012-09-14 Robin J. Evans

A causal model is an abstract representation of a physical system as a directed acyclic graph (DAG), where the statistical dependencies are encoded using a graphical criterion called `d-separation'. Recent work by Wood & Spekkens shows that…

Quantum Physics · Physics 2015-08-10 Jacques Pienaar , Caslav Brukner

The distinguishing number (index) $D(G)$ ($D'(G)$) of a graph $G$ is the least integer $d$ such that $G$ has an vertex labeling (edge labeling) with $d$ labels that is preserved only by a trivial automorphism. Let $G$ be a connected graph…

Combinatorics · Mathematics 2016-07-26 Samaneh Soltani , Saeid Alikhani

We give deterministic distributed $(1+\epsilon)$-approximation algorithms for Minimum Vertex Coloring and Maximum Independent Set on chordal graphs in the LOCAL model. Our coloring algorithm runs in $O(\frac{1}{\epsilon} \log n)$ rounds,…

Data Structures and Algorithms · Computer Science 2018-05-15 Christian Konrad , Viktor Zamaraev

Gaussian graphical models are semi-algebraic subsets of the cone of positive definite covariance matrices. Submatrices with low rank correspond to generalizations of conditional independence constraints on collections of random variables.…

Machine Learning · Statistics 2010-10-05 Seth Sullivant , Kelli Talaska , Jan Draisma

A graph $G$ is said to be $d$-distinguishable if there is a vertex coloring of $G$ with a set of $d$ colors which breaks all of the automorphisms of $G$ but the identity. We call the minimum $d$ for which a graph $G$ is $d$-distinguishiable…

Combinatorics · Mathematics 2019-10-29 Aleksandra Gorzkowska , Mohammad Hadi Shekarriz

The Minimum Path Cover (MPC) problem consists of finding a minimum-cardinality set of node-disjoint paths that cover all nodes in a given graph. We explore a variant of the MPC problem on acyclic digraphs (DAGs) where, given a subset of…

Discrete Mathematics · Computer Science 2025-01-17 Nour ElHouda Tellache , Roberto Baldacci

Neural networks are suggested for learning a map from $d$-dimensional samples with any underlying dependence structure to multivariate uniformity in $d'$ dimensions. This map, termed DecoupleNet, is used for dependence model assessment and…

Machine Learning · Statistics 2022-10-06 Marius Hofert , Avinash Prasad , Mu Zhu

Many NP-Hard problems on general graphs, such as maximum independence set, maximal cliques and graph coloring can be solved efficiently on chordal graphs. In this paper, we explore the problem of non-separating st-paths defined on edges:…

Data Structures and Algorithms · Computer Science 2021-02-10 Xiao Mao

The distinguishing number (index) $D(G)$ ($D'(G)$) of a graph $G$ is the least integer $d$ such that $G$ has an vertex labeling (edge labeling) with $d$ labels that is preserved only by a trivial automorphism. In this paper we compute these…

Combinatorics · Mathematics 2016-07-27 Saeid Alikhani , Samaneh Soltani

The distinguishing index of a simple graph $G$, denoted by $D'(G)$, is the least number of labels in an edge labeling of $G$ not preserved by any non-trivial automorphism. It was conjectured by Pil\'sniak (2015) that for any 2-connected…

Combinatorics · Mathematics 2017-02-14 Saeid Alikhani , Samaneh Soltani

The distinguishing number $D(G)$ of a graph $G$ is the least integer $d$ such that $G$ has an vertex labeling with $d$ labels that is preserved only by a trivial automorphism. A list assignment to $G$ is an assignment $L = \{L(v)\}_{v\in V…

Combinatorics · Mathematics 2017-11-27 Saeid Alikhani , Samaneh Soltani

Learning causal relations from observational data is a fundamental problem with wide-ranging applications across many fields. Constraint-based methods infer the underlying causal structure by performing conditional independence tests.…

Machine Learning · Computer Science 2026-03-24 Marc Franquesa Monés , Jiaqi Zhang , Caroline Uhler
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