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In this paper we study the inverse eigenvector centrality problem on directed graphs: given a prescribed node centrality profile, we seek edge weights that realize it. Since this inverse problem generally admits infinitely many solutions,…

Social and Information Networks · Computer Science 2026-02-13 Mauro Passacantando , Fabio Raciti

Recent papers have formulated the problem of learning graphs from data as an inverse covariance estimation with graph Laplacian constraints. While such problems are convex, existing methods cannot guarantee that solutions will have specific…

Machine Learning · Statistics 2018-05-09 Eduardo Pavez , Hilmi E. Egilmez , Antonio Ortega

In the Graph Reconstruction (GR) problem, the goal is to recover a hidden graph by utilizing some oracle that provides limited access to the structure of the graph. The interest is in characterizing how strong different oracles are when the…

Data Structures and Algorithms · Computer Science 2025-09-15 Juha Harviainen , Pekka Parviainen

In this paper, we study the complexity of the edge monitoring problem. A vertex $v$ monitors an edge $e$ if both extremities together with $v$ form a triangle in the graph. Given a graph $G=(V,E)$ and a weight function on edges $c$ where…

Discrete Mathematics · Computer Science 2017-10-06 Guillaume Bagan , Fairouz Beggas , Mohammed Haddad , Hamamache Kheddouci

The shortest path problem in graphs is a cornerstone of AI theory and applications. Existing algorithms generally ignore edge weight computation time. We present a generalized framework for weighted directed graphs, where edge weight can be…

Data Structures and Algorithms · Computer Science 2024-02-20 Eyal Weiss , Ariel Felner , Gal A. Kaminka

A mixed dominating set of a graph $G = (V, E)$ is a mixed set $D$ of vertices and edges, such that for every edge or vertex, if it is not in $D$, then it is adjacent or incident to at least one vertex or edge in $D$. The mixed domination…

Data Structures and Algorithms · Computer Science 2019-06-27 Mingyu Xiao

We propose an algorithm for deep learning on networks and graphs. It relies on the notion that many graph algorithms, such as PageRank, Weisfeiler-Lehman, or Message Passing can be expressed as iterative vertex updates. Unlike previous…

Machine Learning · Computer Science 2018-06-05 Emmanouil Antonios Platanios , Alex Smola

We consider the problem of learning a general graph $G=(V,E)$ using edge-detecting queries, where the number of vertices $|V|=n$ is given to the learner. The information theoretic lower bound gives $m\log n$ for the number of queries, where…

Machine Learning · Computer Science 2018-03-29 Hasan Abasi , Nader H. Bshouty

We consider the following graph reconstruction problem: given an unweighted connected graph $G = (V,E)$ with visible vertex set $V$ and an oracle which takes two vertices $u,v \in V$ and returns the shortest path distance between $u$ and…

Data Structures and Algorithms · Computer Science 2026-03-12 Chirag Kaudan , Amir Nayyeri

In this paper, we explore the topic of graph learning from the perspective of the Irregularity-Aware Graph Fourier Transform, with the goal of learning the graph signal space inner product to better model data. We propose a novel method to…

Signal Processing · Electrical Eng. & Systems 2023-03-16 Benjamin Girault , Eduardo Pavez , Antonio Ortega

Let $G$ be an undirected graph. An edge of $G$ dominates itself and all edges adjacent to it. A subset $E'$ of edges of $G$ is an edge dominating set of $G$, if every edge of the graph is dominated by some edge of $E'$. We say that $E'$ is…

Discrete Mathematics · Computer Science 2017-05-24 Min Chih Lin , Vadim Lozin , Veronica A. Moyano , Jayme L. Szwarcfiter

We study the structure learning problem for $H$-colorings, an important class of Markov random fields that capture key combinatorial structures on graphs, including proper colorings and independent sets, as well as spin systems from…

Discrete Mathematics · Computer Science 2018-04-25 Antonio Blanca , Zongchen Chen , Daniel Štefankovič , Eric Vigoda

In this paper we discuss reconstruction problems for graphs. We develop some new ideas like isomorphic extension of isomorphic graphs, partitioning of vertex sets into sets of equivalent points, subdeck property, etc. and develop an…

General Mathematics · Mathematics 2011-10-21 Dhananjay P. Mehendale

The congested clique model is a message-passing model of distributed computation where the underlying communication network is the complete graph of $n$ nodes. In this paper we consider the situation where the joint input to the nodes is an…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-06-13 Pedro Montealegre , Sebastian Perez-Salazar , Ivan Rapaport , Ioan Todinca

Let ${\cal G}=(G,w)$ be a weighted simple finite connected graph, that is, let $G$ be a simple finite connected graph endowed with a function $w$ from the set of the edges of $G$ to the set of real numbers. For any subgraph $G'$ of $G$, we…

Combinatorics · Mathematics 2014-12-18 Elena Rubei

Research on graph representation learning has received a lot of attention in recent years since many data in real-world applications come in form of graphs. High-dimensional graph data are often in irregular form, which makes them more…

Machine Learning · Computer Science 2020-06-03 Fenxiao Chen , Yuncheng Wang , Bin Wang , C. -C. Jay Kuo

For a graph G with real weights assigned to the vertices (edges), the MAX H-SUBGRAPH problem is to find an H-subgraph of G with maximum total weight, if one exists. The all-pairs MAX H-SUBGRAPH problem is to find for every pair of vertices…

Data Structures and Algorithms · Computer Science 2007-05-23 Virginia Vassilevska , Ryan Williams , Raphael Yuster

We consider three variants of the problem of finding a maximum weight restricted $2$-matching in a subcubic graph $G$. (A $2$-matching is any subset of the edges such that each vertex is incident to at most two of its edges.) Depending on…

Data Structures and Algorithms · Computer Science 2021-01-01 Katarzyna Paluch , Mateusz Wasylkiewicz

Let $G=(V,E,w)$ be a finite, connected graph with weighted edges. We are interested in the problem of finding a subset $W \subset V$ of vertices and weights $a_w$ such that $$ \frac{1}{|V|}\sum_{v \in V}^{}{f(v)} \sim \sum_{w \in W}{a_w…

Statistics Theory · Mathematics 2018-03-20 George C. Linderman , Stefan Steinerberger

Node classification in graphs aims to predict the categories of unlabeled nodes by utilizing a small set of labeled nodes. However, weighted graphs often contain noisy edges and anomalous edge weights, which can distort fine-grained…

Machine Learning · Computer Science 2025-04-01 Tingting Wang , Jiaxin Su , Haobing Liu , Ruobing Jiang