Publications associées à Graph Transformations preserving the stability number

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Efficient Streaming Subgraph Isomorphism with Graph Neural Networks

Karl Aberer, Quoc Viet Hung Nguyen, Chi Thang Duong, Trung-Dung Hoang

Queries to detect isomorphic subgraphs are important in graph-based data management. While the problem of subgraph isomorphism search has received considerable attention for the static setting of a single query, or a batch thereof, existing approaches do n ...

ASSOC COMPUTING MACHINERY2021

Improved Ramsey-type results for comparability graphs

Istvan Tomon, Dániel József Korándi

Several discrete geometry problems are equivalent to estimating the size of the largest homogeneous sets in graphs that happen to be the union of few comparability graphs. An important observation for such results is that if G is an n-vertex graph that is ...

CAMBRIDGE UNIV PRESS2020

Graph Laplacian Mixture Model

Pascal Frossard, Hermina Petric Maretic

Graph learning methods have recently been receiving increasing interest as means to infer structure in datasets. Most of the recent approaches focus on different relationships between a graph and data sample distributions, mostly in settings where all avai ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Flooding And Diameter In General Weighted Random Graphs

Thomas Mountford, Jacques Saliba

In this paper we study first passage percolation on a random graph model, the configuration model. We first introduce the notions of weighted diameter, which is the maximum of the weighted lengths of all optimal paths between any two vertices in the graph, ...

CAMBRIDGE UNIV PRESS2020

Graph Learning Under Partial Observability

Ali H. Sayed, Augusto José Rabelo Almeida Santos

Many optimization, inference, and learning tasks can be accomplished efficiently by means of decentralized processing algorithms where the network topology (i.e., the graph) plays a critical role in enabling the interactions among neighboring nodes. There ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Fast and Accurate Efficient Streaming Subgraph Isomorphism

Karl Aberer, Quoc Viet Hung Nguyen, Chi Thang Duong, Trung-Dung Hoang

2020

Differentially Private Release of Synthetic Graphs

Mikhail Kapralov, Marek Elias

We propose a (epsilon, delta)-differentially private mechanism that, given an input graph G with n vertices and m edges, in polynomial time generates a synthetic graph G' approximating all cuts of the input graph up to an additive error of O (root mn/epsil ...

ASSOC COMPUTING MACHINERY2020

Adaptive Majority Problems For Restricted Query Graphs And For Weighted Sets

Abhishek Methuku, Balázs Keszegh

Suppose that the vertices of a graph G are colored with two colors in an unknown way. The color that occurs on more than half of the vertices is called the majority color (if it exists), and any vertex of this color is called a majority vertex. We study th ...

COMENIUS UNIV2019

Graph Transformations preserving the stability number

Graph Chatbot

Chattez avec Graph Search

Efficient Streaming Subgraph Isomorphism with Graph Neural Networks

Improved Ramsey-type results for comparability graphs

Edge colorings of graphs without monochromatic stars

Graph Laplacian Mixture Model

Simple Realizability of Complete Abstract Topological Graphs Simplified

Flooding And Diameter In General Weighted Random Graphs

Graph Learning Under Partial Observability

Fast and Accurate Efficient Streaming Subgraph Isomorphism

Differentially Private Release of Synthetic Graphs

Adaptive Majority Problems For Restricted Query Graphs And For Weighted Sets

Improved Ramsey-type results for comparability graphs

Edge colorings of graphs without monochromatic stars

Graph Laplacian Mixture Model

Adaptive Majority Problems For Restricted Query Graphs And For Weighted Sets

Simple Realizability of Complete Abstract Topological Graphs Simplified

Flooding And Diameter In General Weighted Random Graphs

Efficient Streaming Subgraph Isomorphism with Graph Neural Networks

Graph Learning Under Partial Observability

Differentially Private Release of Synthetic Graphs

Fast and Accurate Efficient Streaming Subgraph Isomorphism