Concept

Subgraph isomorphism problem

Related publications (44)

Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs

Combinatorial optimization (CO) problems are notoriously challenging for neural networks, especially in the absence of labeled instances. This work proposes an unsupervised learning framework for CO problems on graphs that can provide integral solutions of ...

2020

RAQ: Relationship-Aware Graph Querying in Large Networks

Akhil Arora, Arnab Bhattacharya

The phenomenal growth of graph data from a wide variety of real-world applications has rendered graph querying to be a problem of paramount importance. Traditional techniques use structural as well as node similarities to find matches of a given query grap ...

ASSOC COMPUTING MACHINERY2019

Graph Learning with Partial Observations: Role of Degree Concentration

Ali H. Sayed, Augusto José Rabelo Almeida Santos

In this work we consider the problem of learning an Erdos-Renyi graph over a diffusion network when: i) data from only a limited subset of nodes are available (partial observation); ii) and the inferential goal is to discover the graph of interconnections ...

IEEE2019

Time-resolved analysis of dynamic graphs: an extended Slepian design

Dimitri Nestor Alice Van De Ville, Raphaël Pierre Liégeois, Ibrahim Merad

Graphs are extensively used to represent networked data. In many applications, especially when considering large datasets, it is a desirable feature to focus the analysis onto specific subgraphs of interest. Slepian theory and its extension to graphs allow ...

SPIE-INT SOC OPTICAL ENGINEERING2019

Analysis of a Canonical Labeling Algorithm for the Alignment of Correlated Erdős-Rényi Graphs

Matthias Grossglauser, Negar Kiyavash, Osman Emre Dai

Graph alignment in two correlated random graphs refers to the task of identifying the correspondence between vertex sets of the graphs. Recent results have characterized the exact information-theoretic threshold for graph alignment in correlated Erdös-Rény ...

Association for Computing Machinery (ACM)2019

Graph Reduction with Spectral and Cut Guarantees

Andreas Loukas

Can one reduce the size of a graph without significantly altering its basic properties? The graph reduction problem is hereby approached from the perspective of restricted spectral approximation, a modification of the spectral similarity measure used for g ...

MICROTOME PUBL2019

The Sketching Complexity of Graph and Hypergraph Counting

Mikhail Kapralov, John Michael Goddard Kallaugher

Subgraph counting is a fundamental primitive in graph processing, with applications in social network analysis (e.g., estimating the clustering coefficient of a graph), database processing and other areas. The space complexity of subgraph counting has been ...

IEEE COMPUTER SOC2018

Apartment Structure Estimation Using Fully Convolutional Networks and Graph Model

Jing Zhang

Apartment searching has been a hot demand all over the world. Understanding the apartment structure will significantly contribute to simplifying the searching process. In this project, the fully convolutional networks are applied to generate semantic segme ...

ASSOC COMPUTING MACHINERY2018

Phonological Posterior Hashing for Query by Example Spoken Term Detection

Hervé Bourlard, Afsaneh Asaei, Dhananjay Ram

State of the art query by example spoken term detection (QbE-STD) systems in zero-resource conditions rely on representation of speech in terms of sequences of class-conditional posterior probabilities estimated by deep neural network (DNN). The posteriors ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Adventures in Monotone Complexity and TFNP

Mika Tapani Göös, Dmitrii Sokolov

Separations: We introduce a monotone variant of Xor-Sat and show it has exponential monotone circuit complexity. Since Xor-Sat is in NC^2, this improves qualitatively on the monotone vs. non-monotone separation of Tardos (1988). We also show that monotone ...

Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany2018

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