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On the Correlation of Graph Edit Distance and L 1 Distance in the Attribute Statistics Embedding Space
[chapter]

2012
*
Lecture Notes in Computer Science
*

*In*this work, we analyse relations between

*the*

*edit*

*distance*

*in*

*the*

*graph*domain

*and*

*the*L1

*distance*

*of*

*the*

*attribute*

*statistics*based

*embedding*, for which good classification performance has been reported ...

*Graph*

*embeddings*

*in*vector

*spaces*aim at assigning a pattern vector to every

*graph*so that

*the*problems

*of*

*graph*classification

*and*clustering can be solved by using data processing algorithms originally ... Conclusions

*In*this work we have established a relation between

*graph*

*edit*

*distance*

*and*

*the*

*L*

*1*vectorial

*distance*

*in*

*the*

*attribute*

*statistics*

*embedding*

*space*. ...

##
###
Graph Self-supervised Learning with Accurate Discrepancy Learning
[article]

2022
*
arXiv
*
pre-print

Moreover, we further aim to accurately capture

arXiv:2202.02989v2
fatcat:7x2xshtofvbjlobnqzngkxkosm
*the*amount*of*discrepancy for each perturbed*graph*using*the**graph**edit**distance*. ... Specifically, we create multiple perturbations*of**the*given*graph*with varying degrees*of*similarity*and*train*the*model to predict whether each*graph*is*the*original*graph*or a perturbed*one*. ... After that, we learn GNNs to distinguish perturbed*graphs*from original*ones*, but also accurately discriminate*the*original, perturbed,*and*other*graphs**in**the**embedding**space*with their*distances*. into ...##
###
A Comparison of Explicit and Implicit Graph Embedding Methods for Pattern Recognition
[chapter]

2013
*
Lecture Notes in Computer Science
*

*In*this paper we present a comparison

*of*two implicit

*and*three explicit state

*of*

*the*art

*graph*

*embedding*methodologies. ... expensive

*and*efficient state

*of*

*the*art machine learning models

*of*

*statistical*pattern recognition. ... Method 3:

*Attribute*

*Statistics*based

*Embedding*

*The*

*attribute*

*statistics*based

*embedding*

*of*

*graphs*is a simple

*and*efficient way

*of*expressing

*the*labelling information stored

*in*nodes

*and*edges

*of*

*graphs*...

##
###
On the Use of the Chi-Squared Distance for the Structured Learning of Graph Embeddings

2011
*
2011 International Conference on Digital Image Computing: Techniques and Applications
*

*In*this paper, we describe

*the*use

*of*concepts from

*the*areas

*of*structural

*and*

*statistical*pattern recognition for

*the*purposes

*of*recovering a mapping which can be viewed as an operator

*on*

*the*

*graph*... This treatment leads to

*the*recovery

*of*a mapping based upon

*the*

*graph*

*attributes*which is related to

*the*edge-

*space*

*of*

*the*

*graphs*under study. ... We recover this

*embedding*making use

*of*

*the*Chi-squared

*distance*

*and*

*statistical*learning techniques. ...

##
###
A Structured Learning Approach to Attributed Graph Embedding
[chapter]

2010
*
Lecture Notes in Computer Science
*

*In*this paper, we describe

*the*use

*of*concepts from structural

*and*

*statistical*pattern recognition for recovering a mapping which can be viewed as an operator

*on*

*the*

*graph*

*attribute*-set. ... We illustrate

*the*utility

*of*

*the*recovered

*embedding*for shape matching

*and*categorisation

*on*MPEG7 CE-Shape-

*1*dataset. We also compare our results to those yielded by alternatives. ... He is supported by

*the*National Natural Science Foundation

*of*China (NSFC) under No.60775015. ...

##
###
Spectral embedding of graphs

2003
*
Pattern Recognition
*

We illustrate

doi:10.1016/s0031-3203(03)00084-0
fatcat:35bjtqgclbag3kmyo5hhoyexi4
*the*utility*of**the**embedding*methods*on*neighbourhood*graphs*representing*the*arrangement*of*corner features*in*2D images*of*3D polyhedral objects. Two problems are investigated. ... These two studies reveal that both*embedding*methods result*in*well-structured view*spaces*for*graph*-data extracted from 2D views*of*3D objects. ... Unfortunately,*and*for*the*reasons noted above,*the*process*of**embedding**graphs**in*a vector-*space*is not a straightforward*one*. ...##
###
On Palimpsests in Neural Memory: An Information Theory Viewpoint

2016
*
IEEE Transactions on Molecular, Biological and Multi-Scale Communications
*

We examine

doi:10.1109/tmbmc.2016.2640320
dblp:journals/tmbmc/VarshneyKG16
fatcat:5zutgffzazbpbaxcqkeutlha7u
*the*tradeoff between compression efficiency*and*malleability cost, under a malleability metric defined with respect to a string*edit**distance*. ... a new*one*. ... Now we are concerned with*the*error-tolerant*embedding**of*an*attributed*, weighted source adjacency*graph*into*the**graph*induced by a V * -*space**edit**distance*. ...##
###
Concept Drift and Anomaly Detection in Graph Streams

2018
*
IEEE Transactions on Neural Networks and Learning Systems
*

*In*addition, we provide a specific implementation

*of*

*the*methodology

*and*evaluate its effectiveness

*on*several detection problems involving

*attributed*

*graphs*representing biological molecules

*and*drawings ...

*The*methodology is general

*and*considers a process generating

*attributed*

*graphs*with a variable number

*of*vertices/edges, without

*the*need to assume

*one*-to-

*one*correspondence between vertices at different ... A well-known family

*of*algorithms used to assess dissimilarity between

*graphs*relies

*on*

*the*

*Graph*

*Edit*

*Distance*(GED) approach [27] . ...

##
###
Generalized median graph computation by means of graph embedding in vector spaces

2010
*
Pattern Recognition
*

*In*this paper we propose a new approach for

*the*computation

*of*

*the*median

*graph*based

*on*

*graph*

*embedding*.

*Graphs*are

*embedded*into a vector

*space*

*and*

*the*median is computed

*in*

*the*vector domain. ... We have designed a procedure based

*on*

*the*weighted mean

*of*a pair

*of*

*graphs*to go from

*the*vector domain back to

*the*

*graph*domain

*in*order to obtain a final approximation

*of*

*the*median

*graph*. ... Kaspar Riesen

*and*Horst Bunke like to acknowledge support from

*the*Swiss National Science Foundation (Project 200021-113198/

*1*). ...

##
###
Comparing the Preservation of Network Properties by Graph Embeddings
[chapter]

2020
*
Lecture Notes in Computer Science
*

We show that most

doi:10.1007/978-3-030-44584-3_41
fatcat:yhhmurryoff5xde5oldoxzgqha
*of**the*algorithms are able to recover at most*one**of**the*properties*and*that some algorithms are more sensitive to*the**embedding**space*dimension than some others. ...*Graph**embedding*is a technique which consists*in*finding a new representation for a*graph*usually by representing*the*nodes as vectors*in*a low-dimensional real*space*. ... This work has been supported by BITUNAM Project ANR-18-CE23-0004*and*IDEXLYON ACADEMICS Project ANR-16-IDEX-0005*of**the*French National Research Agency. ...##
###
Approximate graph edit distance computation by means of bipartite graph matching

2009
*
Image and Vision Computing
*

*The*key advantages

*of*

*graph*

*edit*

*distance*are its high degree

*of*flexibility, which makes it applicable to any type

*of*

*graph*,

*and*

*the*fact that

*one*can integrate domain specific knowledge about object ... Its computational complexity, however, is exponential

*in*

*the*number

*of*nodes

*of*

*the*involved

*graphs*. Consequently, exact

*graph*

*edit*

*distance*is feasible for

*graphs*

*of*rather small size only. ... (

*Graph*

*Edit*

*Distance*) Let g

*1*¼ ðV

*1*; E

*1*;

*l*

*1*; m

*1*Þ be

*the*source

*and*g 2 ¼ ðV 2 ; E 2 ;

*l*2 ; m 2 Þ

*the*target

*graph*. ...

##
###
A generic framework for median graph computation based on a recursive embedding approach

2011
*
Computer Vision and Image Understanding
*

*In*order to evaluate

*the*proposed method, we compare it with

*the*set median

*and*with

*the*other state-

*of*-

*the*-art

*embedding*-based methods for

*the*median

*graph*computation. ... Recently,

*graph*

*embedding*into vector

*spaces*has been proposed to obtain approximations

*of*

*the*median

*graph*. ... Acknowledgments This work has been supported by

*the*Spanish research programmes Consolider Ingenio 2010 CSD2007-00018, TIN2006-15694-C02-02

*and*TIN2008-04998

*and*

*the*fellowship RYC-2009-05031. ...

##
###
Graph edit distance: Accuracy of local branching from an application point of view

2018
*
Pattern Recognition Letters
*

*In*

*the*context

*of*

*graph*-based representations, comparing

*and*measuring

*the*dissimilarities between

*graphs*can be done by solving

*the*

*Graph*

*Edit*

*Distance*(GED) problem. ...

*In*this work,

*the*focus is

*on*evaluating LocBra with other competitive heuristics available

*in*

*the*literature from an application point

*of*view. ...

*One*

*of*

*the*most important problems that belongs to ETGM class is

*the*

*Graph*

*Edit*

*Distance*(GED). ...

##
###
node2bits: Compact Time- and Attribute-aware Node Representations for User Stitching
[article]

2019
*
arXiv
*
pre-print

Extensive experiments

arXiv:1904.08572v2
fatcat:ialligoyrzfqbhehghnn6vhm2e
*on*large-scale real networks show that node2bits outperforms traditional techniques*and*existing works that generate real-valued*embeddings*by up to 5.16%*in*F1 score*on*user stitching ... To solve*the*problem*in*an application-independent way, we take a heterogeneous network-based approach*in*which users (nodes) interact with content (e.g., sessions, websites),*and*may have*attributes*( ... Any opinions, findings,*and*conclusions or recommendations expressed*in*this material are those*of**the*author(s)*and*do not necessarily reflect*the*views*of**the*NSF or other funding parties. ...##
###
Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity
[article]

2019
*
arXiv
*
pre-print

Experiments

arXiv:1904.01098v2
fatcat:atdqtznunbbo3p6xvywnucsun4
*on*five real*graph*datasets show that UGRAPHEMB achieves competitive accuracy*in**the*tasks*of**graph*classification, similarity ranking,*and**graph*visualization. ... We introduce a novel approach to*graph*-level representation learning, which is to embed an entire*graph*into a vector*space*where*the**embeddings**of*two*graphs*preserve their*graph*-*graph*proximity. ... C.2*GRAPH**EDIT**DISTANCE*(GED)*The**edit**distance*between two*graphs*(Bunke, 1983 ) G*1**and*G 2 is*the*number*of**edit*operations*in**the*optimal alignments that transform G*1*into G 2 , where an*edit*operation ...
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