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The Resource Maximum-Entropy Networks : Pattern Detection, Network Reconstruction and Graph Combinatorics, by Tiziano Squartini, Diego Garlaschelli, (electronic resource)

Maximum-Entropy Networks : Pattern Detection, Network Reconstruction and Graph Combinatorics, by Tiziano Squartini, Diego Garlaschelli, (electronic resource)

Label
Maximum-Entropy Networks : Pattern Detection, Network Reconstruction and Graph Combinatorics
Title
Maximum-Entropy Networks
Title remainder
Pattern Detection, Network Reconstruction and Graph Combinatorics
Statement of responsibility
by Tiziano Squartini, Diego Garlaschelli
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Language
eng
Summary
This book is an introduction to maximum-entropy models of random graphs with given topological properties and their applications. Its original contribution is the reformulation of many seemingly different problems in the study of both real networks and graph theory within the unified framework of maximum entropy. Particular emphasis is put on the detection of structural patterns in real networks, on the reconstruction of the properties of networks from partial information, and on the enumeration and sampling of graphs with given properties.  After a first introductory chapter explaining the motivation, focus, aim and message of the book, chapter 2 introduces the formal construction of maximum-entropy ensembles of graphs with local topological constraints. Chapter 3 focuses on the problem of pattern detection in real networks and provides a powerful way to disentangle nontrivial higher-order structural features from those that can be traced back to simpler local constraints. Chapter 4 focuses on the problem of network reconstruction and introduces various advanced techniques to reliably infer the topology of a network from partial local information. Chapter 5 is devoted to the reformulation of certain 2hard3 combinatorial operations, such as the enumeration and unbiased sampling of graphs with given constraints, within a 2softened3 maximum-entropy framework. A final chapter offers various overarching remarks and take-home messages. By requiring no prior knowledge of network theory, the book targets a broad audience ranging from PhD students approaching these topics for the first time to senior researchers interested in the application of advanced network techniques to their field
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Literary form
non fiction
Series statement
SpringerBriefs in Complexity,
Maximum-Entropy Networks : Pattern Detection, Network Reconstruction and Graph Combinatorics, by Tiziano Squartini, Diego Garlaschelli, (electronic resource)
Label
Maximum-Entropy Networks : Pattern Detection, Network Reconstruction and Graph Combinatorics, by Tiziano Squartini, Diego Garlaschelli, (electronic resource)
Link
http://libproxy.rpi.edu/login?url=http://dx.doi.org/10.1007/978-3-319-69438-2
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mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
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not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Introduction -- Maximum-entropy ensembles of graphs -- Constructing constrained graph ensembles: why and how? -- Comparing models obtained from different constraints -- Pattern detection -- Detecting assortativity and clustering -- Detecting dyadic motifs -- Detecting triadic motifs -- Some extensions to weighted networks -- Network reconstruction -- Reconstructing network properties from partial information -- The Enhanced Configuration Model -- Further reducing the observational requirements -- Graph combinatorics -- A dual route to combinatorics? -- {u2018}Soft{u2019} combinatorial enumeration -- Quantifying ensemble (non)equivalence -- Breaking of equivalence between ensembles -- Implications of (non)equivalence for combinatorics -- 2What then shall we choose?3 Hardness or softness? -- Concluding remarks
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{'f': 'http://opac.lib.rpi.edu/record=b4379982'}
Extent
XII, 116 p. 34 illus., 31 illus. in color.
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multiple file formats
Form of item
electronic
Isbn
9783319694382
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uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
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online resource.
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remote

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