English
Related papers

Related papers: Characterizing DAG-depth of Directed Graphs

200 papers

In this paper, we revisit the split decomposition of graphs and give new combinatorial and algorithmic results for the class of totally decomposable graphs, also known as the distance hereditary graphs, and for two non-trivial subclasses,…

Discrete Mathematics · Computer Science 2011-04-19 Emeric Gioan , Christophe Paul

Estimation of the skeleton of a directed acyclic graph (DAG) is of great importance for understanding the underlying DAG and causaleffects can be assessed from the skeleton when the DAG is notidentifiable. We propose a novel method named…

Methodology · Statistics 2014-05-08 Min Jin Ha , Wei Sun , Jichun Xie

While visual comparison of directed acyclic graphs (DAGs) is commonly encountered in various disciplines (e.g., finance, biology), knowledge about humans' perception of graph similarity is currently quite limited. By graph similarity…

Human-Computer Interaction · Computer Science 2017-09-07 Kathrin Ballweg , Margit Pohl , Günter Wallner , Tatiana von Landesberger

We prove new theoretical results about several variations of the cop and robber game on graphs. First, we consider a variation of the cop and robber game which is more symmetric called the cop and killer game. We prove for all $c < 1$ that…

Discrete Mathematics · Computer Science 2017-11-01 Espen Slettnes , Carl Joshua Quines , Shen-Fu Tsai , Jesse Geneson

The treewidth of a graph is an important invariant in structural and algorithmic graph theory. This paper studies the treewidth of line graphs. We show that determining the treewidth of the line graph of a graph $G$ is equivalent to…

Combinatorics · Mathematics 2014-09-25 Daniel J. Harvey , David R. Wood

We study reachability and shortest paths problems in dynamic directed graphs. Whereas algebraic dynamic data structures supporting edge updates and reachability/distance queries have been known for quite a long time, they do not, in…

Data Structures and Algorithms · Computer Science 2022-04-01 Adam Karczmarz , Anish Mukherjee , Piotr Sankowski

Directed Gaussian graphical models are statistical models that use a directed acyclic graph (DAG) to represent the conditional independence structures between a set of jointly normal random variables. The DAG specifies the model through…

Commutative Algebra · Mathematics 2022-08-08 Pratik Misra , Seth Sullivant

Acyclic model, often depicted as a directed acyclic graph (DAG), has been widely employed to represent directional causal relations among collected nodes. In this article, we propose an efficient method to learn linear non-Gaussian DAG in…

Machine Learning · Statistics 2021-11-02 Ruixuan Zhao , Xin He , Junhui Wang

We consider a cops and robber game where the cops are blocking edges of a graph, while the robber occupies its vertices. At each round of the game, the cops choose some set of edges to block and right after the robber is obliged to move to…

Discrete Mathematics · Computer Science 2020-09-09 Stratis Limnios , Christophe Paul , Joanny Perret , Dimitrios M. Thilikos

\textsc{Cops and Robber} is a game played on graphs where a set of \textit{cops} aim to \textit{capture} the position of a single \textit{robber}. The main parameter of interest in this game is the \textit{cop number}, which is the minimum…

Combinatorics · Mathematics 2025-12-29 Harmender Gahlawat

In this work, we are interested in structure learning for a set of spatially distributed dynamical systems, where individual subsystems are coupled via latent variables and observed through a filter. We represent this model as a directed…

Artificial Intelligence · Computer Science 2016-11-03 Oliver M. Cliff , Mikhail Prokopenko , Robert Fitch

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

Bayesian networks, with structure given by a directed acyclic graph (DAG), are a popular class of graphical models. However, learning Bayesian networks from discrete or categorical data is particularly challenging, due to the large…

Methodology · Statistics 2018-02-06 Jiaying Gu , Fei Fu , Qing Zhou

Learning the structure of directed acyclic graphs (DAGs) from observational data is a central problem in causal discovery, statistical signal processing, and machine learning. Under a linear Gaussian structural equation model (SEM) with…

Machine Learning · Computer Science 2026-05-27 Hamed Ajorlou , Samuel Rey , Gonzalo Mateos , Geert Leus , Antonio G. Marques

With huge amounts of training data, deep learning has made great breakthroughs in many artificial intelligence (AI) applications. However, such large-scale data sets present computational challenges, requiring training to be distributed on…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-11-01 Shaohuai Shi , Qiang Wang , Xiaowen Chu , Bo Li

Directed acyclic graphs (DAGs) are central to science and engineering applications including causal inference, scheduling, and neural architecture search. In this work, we introduce the DAG Convolutional Network (DCN), a novel graph neural…

Signal Processing · Electrical Eng. & Systems 2026-05-20 Samuel Rey , Hamed Ajorlou , Gonzalo Mateos

Learning directed acyclic graph (DAG) that describes the causality of observed data is a very challenging but important task. Due to the limited quantity and quality of observed data, and non-identifiability of causal graph, it is almost…

Machine Learning · Computer Science 2022-11-23 Dezhi Yang , Guoxian Yu , Jun Wang , Zhengtian Wu , Maozu Guo

Over the past decade, we witness an increasing amount of interest in the design of exact exponential-time and parameterized algorithms for problems in Graph Drawing. Unfortunately, we still lack knowledge of general methods to develop such…

Data Structures and Algorithms · Computer Science 2023-10-10 Siddharth Gupta , Guy Sa'ar , Meirav Zehavi

Finding the origin of short phrases propagating through the web has been formalized by Leskovec et al. [ACM SIGKDD 2009] as DAG Partitioning: given an arc-weighted directed acyclic graph on $n$ vertices and $m$ arcs, delete arcs with total…

Data Structures and Algorithms · Computer Science 2017-02-02 René van Bevern , Robert Bredereck , Morgan Chopin , Sepp Hartung , Falk Hüffner , André Nichterlein , Ondřej Suchý

We consider the PC-algorithm Spirtes et. al. (2000) for estimating the skeleton of a very high-dimensional acyclic directed graph (DAG) with corresponding Gaussian distribution. The PC-algorithm is computationally feasible for sparse…

Statistics Theory · Mathematics 2007-06-13 Markus Kalisch , Peter Buehlmann