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Related papers: Algorithms for Enumerating Balanced Tanner Graphs

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The class of 2-interval graphs has been introduced for modelling scheduling and allocation problems, and more recently for specific bioinformatic problems. Some of those applications imply restrictions on the 2-interval graphs, and justify…

Discrete Mathematics · Computer Science 2008-02-04 Philippe Gambette , Stéphane Vialette

We provide algorithms involving edge slides, for a connected simple graph to evolve in a finite number of steps to another connected simple graph in a prescribed configuration, and for the regularization of such a graph by the minimization…

Combinatorics · Mathematics 2010-02-08 Paul Baird , Marius Tiba

This note describes an algorithm for enumerating all the elements in a finite set based on uniformly random sampling from the set. This algorithm can be used for enumeration by fair sampling with quantum annealing. Our algorithm is based on…

Quantum Physics · Physics 2021-04-06 Yuta Mizuno , Tamiki Komatsuzaki

Balanced partitioning is often a crucial first step in solving large-scale graph optimization problems, e.g., in some cases, a big graph can be chopped into pieces that fit on one machine to be processed independently before stitching the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-12-10 Kevin Aydin , MohammadHossein Bateni , Vahab Mirrokni

Generative models of graph structure have applications in biology and social sciences. The state of the art is GraphRNN, which decomposes the graph generation process into a series of sequential steps. While effective for modest sizes, it…

Machine Learning · Computer Science 2019-10-18 Tony Duan , Juho Lee

A new method involving particle diagrams is introduced and developed into a rigorous framework for carrying out embedded random matrix calculations. Using particle diagrams and the attendant methodology including loop counting it becomes…

Quantum Physics · Physics 2015-04-01 Rupert A Small

We extend the notion of an enumeration scheme developed by Zeilberger and Vatter to the case of vincular patterns (also called "generalized patterns" or "dashed patterns"). In particular we provide an algorithm which takes in as input a set…

Combinatorics · Mathematics 2012-01-17 Andrew M. Baxter , Lara K. Pudwell

Novel constructions of empirical controllability and observability gramians for nonlinear systems for subsequent use in a balanced truncation style of model reduction are proposed. The new gramians are based on a generalisation of the…

Optimization and Control · Mathematics 2007-05-23 Marissa Condon , Rossen I. Ivanov

A balanced graph is a bipartite graph with no induced circuit of length 2 mod 4. These graphs arise in linear programming. We focus on graph-algebraic properties of balanced graphs to prove a complete classification of balanced Cayley…

Combinatorics · Mathematics 2007-07-03 Joy Morris , Pablo Spiga , Kerri Webb

In this article we give an in depth overview of the recent advances in the field of equilibrium networks. After outlining this topic, we provide a novel way of defining equilibrium graph (network) ensembles. We illustrate this concept on…

Statistical Mechanics · Physics 2007-05-23 I. Farkas , I. Derenyi , G. Palla , T. Vicsek

Using the theory of combinatorial species, we compute the cycle index for bipartite graphs, which we use to count unlabeled bipartite graphs and bipartite blocks.

Combinatorics · Mathematics 2015-09-14 Andrew Gainer-Dewar , Ira M. Gessel

In the last decade, subgraph detection and enumeration have emerged as a central problem in distributed graph algorithms. This is largely due to the theoretical challenges and practical applications of these problems. In this paper, we…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-23 Duncan Adamson , Will Rosenbaum , Paul G. Spirakis

We consider the problem of enumerating all instances of a given pattern graph in a large data graph. Our focus is on determining the input/output (I/O) complexity of this problem. Let $E$ be the number of edges in the data graph, $k=O(1)$…

Data Structures and Algorithms · Computer Science 2015-11-13 Francesco Silvestri

The goal of this paper is to derive the detailed description of the Enumeration Based Search Algorithm from the high level description provided in [16], analyze the experimental results from our implementation of the Enumeration Based…

Discrete Mathematics · Computer Science 2013-02-26 Vivek S Nittoor , Reiji Suda

Graph-based semantic representations are valuable in natural language processing, where it is often simple and effective to represent linguistic concepts as nodes, and relations as edges between them. Several attempts has been made to find…

Formal Languages and Automata Theory · Computer Science 2021-05-10 Johanna Björklund , Frank Drewes , Anna Jonsson

Traditionally, graph neural networks have been trained using a single observed graph. However, the observed graph represents only one possible realization. In many applications, the graph may encounter uncertainties, such as having…

Machine Learning · Computer Science 2024-10-10 See Hian Lee , Feng Ji , Kelin Xia , Wee Peng Tay

Given a graph $G$, the maximal induced subgraphs problem asks to enumerate all maximal induced subgraphs of $G$ that belong to a certain hereditary graph class. While its optimization version, known as the minimum vertex deletion problem in…

Data Structures and Algorithms · Computer Science 2020-04-22 Yixin Cao

Let $G$ be an $n$-vertex graph, and $s,t$ vertices of $G$. We present an efficient algorithm which enumerates the set of minimal $st$-separators of $G$ in ascending order of cardinality, with a delay of $O(n^{3.5})$ per separator. In…

Data Structures and Algorithms · Computer Science 2021-12-03 Batya Kenig

Recently, working on the Tanner graph which represents a low density parity check (LDPC) code becomes an interesting research subject. Finding the number of short cycles of Tanner graphs motivated Blake and Lin to investigate the…

Discrete Mathematics · Computer Science 2018-08-07 Mohsen Alinejad , Kazem Khashyarmanesh

Graph neural networks (GNNs) are emerging for machine learning research on graph-structured data. GNNs achieve state-of-the-art performance on many tasks, but they face scalability challenges when it comes to real-world applications that…

Machine Learning · Computer Science 2026-04-02 Shichang Zhang , Atefeh Sohrabizadeh , Cheng Wan , Zijie Huang , Ziniu Hu , Yewen Wang , Yingyan , Lin , Jason Cong , Yizhou Sun