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130424s2013 riua ob 100 0 eng d |
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|d K6U
|d OCLCO
|d OCLCQ
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|z 9780821890387
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|a MAT
|x 000000
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0 |
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|a 511/.5
|2 23
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084 |
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|a 05C85
|a 68W05
|a 05C82
|a 68W10
|a 68R10
|a 05C50
|a 05C65
|2 msc
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049 |
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|a UAMI
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111 |
2 |
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|a DIMACS Implementation Challenge Workshop
|n (10th :
|d 2012 :
|c Atlanta, Ga.)
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245 |
1 |
0 |
|a Graph partitioning and graph clustering :
|b 10th DIMACS Implementation Challenge Workshop, February 13-14, 2012, Georgia Institute of Technology, Atlanta, GA /
|c David A. Bader, Henning Meyerhenke, Peter Sanders, Dorothea Wagner, editors.
|
264 |
|
1 |
|a Providence, Rhode Island :
|b American Mathematical Society,
|c [2013]
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264 |
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4 |
|c ©2013
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300 |
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|a 1 online resource (xiii, 240 pages) :
|b illustrations (some color)
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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338 |
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|a online resource
|b cr
|2 rdacarrier
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490 |
1 |
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|a Contemporary mathematics,
|x 0271-4132 ;
|v 588
|
504 |
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|a Includes bibliographical references.
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588 |
0 |
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|a Print version record.
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505 |
0 |
0 |
|t High quality graph partitioning /
|r Peter Sanders and Christian Schulz --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11700
|t Abusing a hypergraph partitioner for unweighted graph partitioning /
|r B. O. Fagginger Auer and R. H. Bisseling --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11707
|t Parallel partitioning with Zoltan: Is hypergraph partitioning worth it? /
|r Sivasankaran Rajamanickam and Erik G. Boman --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11711
|t UMPa: A multi-objective, multi-level partitioner for communication minimization /
|r Ümit V. Çatalyürek, Mehmet Deveci, Kamer Kaya and Bora Uçar --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11704
|t Shape optimizing load balancing for MPI-parallel adaptive numerical simulations /
|r Henning Meyerhenke --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11699
|t Graph partitioning for scalable distributed graph computations /
|r Aydın Buluç and Kamesh Madduri --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11709
|t Using graph partitioning for efficient network modularity optimization /
|r Hristo Djidjev and Melih Onus --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11713
|t Modularity maximization in networks by variable neighborhood search /
|r Daniel Aloise, Gilles Caporossi, Pierre Hansen, Leo Liberti, Sylvain Perron and Manuel Ruiz --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11705
|t Network clustering via clique relaxations: A community based approach /
|r Anurag Verma and Sergiy Butenko --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11702
|t Identifying base clusters and their application to maximizing modularity /
|r Sriram Srinivasan, Tanmoy Chakraborty and Sanjukta Bhowmick --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11708
|t Complete hierarchical cut-clustering: A case study on expansion and modularity /
|r Michael Hamann, Tanja Hartmann and Dorothea Wagner --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11710
|t A partitioning-based divisive clustering technique for maximizing the modularity /
|r Ümit V. Çatalyürek, Kamer Kaya, Johannes Langguth and Bora Uçar --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11712
|t An ensemble learning strategy for graph clustering /
|r Michael Ovelgönne and Andreas Geyer-Schulz --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11701
|t Parallel community detection for massive graphs /
|r E. Jason Riedy, Henning Meyerhenke, David Ediger and David A. Bader --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11703
|t Graph coarsening and clustering on the GPU /
|r B. O. Fagginger Auer and R. H. Bisseling --
|u http://www.ams.org/conm/588/
|u http://dx.doi.org/10.1090/conm/588/11706
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520 |
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|a "Graph partitioning and graph clustering are ubiquitous subtasks in many applications where graphs play an important role. Generally speaking, both techniques aim at the identification of vertex subsets with many internal and few external edges. To name only a few, problems addressed by graph partitioning and graph clustering algorithms are: What are the communities within an (online) social network? ; How do I speed up a numerical simulation by mapping it efficiently onto a parallel computer? ; How must components be organized on a computer chip such that they can communicate efficiently with each other? ; What are the segments of a digital image? ; Which functions are certain genes (most likely) responsible for?. The 10th DIMACS Implementation Challenge Workshop was devoted to determining realistic performance of algorithms where worst case analysis is overly pessimistic and probabilistic models are too unrealistic. Articles in the volume describe and analyze various experimental data with the goal of getting insight into realistic algorithm performance in situations where analysis fails. This book is published in cooperation with the Center for Discrete Mathematics and Theoretical Computer Science."--Publisher's website.
|
546 |
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|a English.
|
590 |
|
|
|a ProQuest Ebook Central
|b Ebook Central Academic Complete
|
650 |
|
0 |
|a Graph algorithms
|v Congresses.
|
650 |
|
0 |
|a Graph theory
|v Congresses.
|
650 |
|
6 |
|a Algorithmes de graphes
|v Congrès.
|
650 |
|
7 |
|a MATHEMATICS
|x General.
|2 bisacsh
|
650 |
|
7 |
|a Graph algorithms
|2 fast
|
650 |
|
7 |
|a Graph theory
|2 fast
|
650 |
|
7 |
|a Combinatorics
|x Graph theory
|x Graph algorithms.
|2 msc
|
650 |
|
7 |
|a Computer science
|x Algorithms
|x Nonnumerical algorithms.
|2 msc
|
650 |
|
7 |
|a Combinatorics
|x Graph theory
|x Small world graphs, complex networks.
|2 msc
|
650 |
|
7 |
|a Computer science
|x Algorithms
|x Parallel algorithms.
|2 msc
|
650 |
|
7 |
|a Computer science
|x Discrete mathematics in relation to computer science
|x Graph theory (including graph drawing)
|2 msc
|
650 |
|
7 |
|a Combinatorics
|x Graph theory
|x Graphs and linear algebra (matrices, eigenvalues, etc.)
|2 msc
|
650 |
|
7 |
|a Combinatorics
|x Graph theory
|x Hypergraphs.
|2 msc
|
655 |
|
7 |
|a Conference papers and proceedings
|2 fast
|
700 |
1 |
|
|a Bader, David A.,
|d 1969-
|e editor.
|1 https://id.oclc.org/worldcat/entity/E39PCjHHjjFMMDj9BcJYkWKKMK
|
700 |
1 |
|
|a Meyerhenke, Henning,
|d 1978-
|e editor.
|1 https://id.oclc.org/worldcat/entity/E39PCjCRhPRJtT7w44CRQqwQYK
|
700 |
1 |
|
|a Sanders, Peter,
|d 1967-
|e editor.
|1 https://id.oclc.org/worldcat/entity/E39PBJwHc74d3XyXgj8kBtyDbd
|
700 |
1 |
|
|a Wagner, Dorothea,
|d 1957-
|e editor.
|1 https://id.oclc.org/worldcat/entity/E39PBJqbkBFcDvBXbqqmYVhfv3
|
758 |
|
|
|i has work:
|a Graph partitioning and graph clustering (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGWWHD8VCWbp7kMtpTvktC
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
776 |
0 |
8 |
|i Print version:
|a DIMACS Implementation Challenge Workshop (10th : 2012 : Atlanta, Ga.).
|t Graph partitioning and graph clustering
|z 9780821890387
|w (DLC) 2012048265
|w (OCoLC)829644505
|
830 |
|
0 |
|a Contemporary mathematics (American Mathematical Society) ;
|v v. 588.
|
856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=3113242
|z Texto completo
|
938 |
|
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|a ProQuest Ebook Central
|b EBLB
|n EBL3113242
|
938 |
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|a EBSCOhost
|b EBSC
|n 974712
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938 |
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|a YBP Library Services
|b YANK
|n 11847448
|
938 |
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|a Internet Archive
|b INAR
|n graphpartitionin0000dima
|
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|a 92
|b IZTAP
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