Celebrating Fifty Years of David M. Young’s Successive Overrelaxation Method View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2004

AUTHORS

David R. Kincaid

ABSTRACT

It has been over fifty years since David M. Young’s original work on the successive overrelaxation (SOR) methods. This fundamental method now appears in all textbooks containing an introductory discussion of iterative solution methods. (Most often the SOR method appears after a presentation of Jacobi iteration and Gauss-Seidel iteration and before the conjugate gradient iterative method.) We present a brief survey of some of the research of Professor David M. Young, together with his students and collaborators, on iterative methods for solving large sparse linear algebraic equations. This is not a complete survey but just a sampling of various papers with a focus on some of these publications. Dr. David M. Young’s doctoral thesis [27] was accepted in 1950 by his supervising Professor Garrett Birkhoff of Harvard University and his paper [28] based this work appeared in 1954. This is one of the landmark contributions in modern numerical analysis. The red-black ordering for matrices is of great importance in parallel computing. Gene Golub has said: “It’s almost as if David could see into the future!” David Young celebrated his 80th birthday on October 20, 2003 (http://www.ma.utexas.edu/CNA/photos.html). More... »

PAGES

549-558

References to SciGraph publications

Book

TITLE

Numerical Mathematics and Advanced Applications

ISBN

978-3-642-62288-5
978-3-642-18775-9

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-18775-9_52

DOI

http://dx.doi.org/10.1007/978-3-642-18775-9_52

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1049971290


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Numerical and Computational Mathematics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "The University of Texas at Austin", 
          "id": "https://www.grid.ac/institutes/grid.89336.37", 
          "name": [
            "Department of Computer Sciences, University of Texas at Austin, 78712, Austin, Texas, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kincaid", 
        "givenName": "David R.", 
        "id": "sg:person.013745557321.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013745557321.27"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1145/356004.356009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001863832"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01386013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002672967", 
          "https://doi.org/10.1007/bf01386013"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-1-4832-0078-1.50021-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003495274"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1090/s0025-5718-1970-0281331-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004224954"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0377-0427(88)90347-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014678091"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1090/s0025-5718-1972-0311089-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014807608"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0065-2458(08)60620-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015190251"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0377-0427(96)00030-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017065682"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0024-3795(80)90165-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017293764"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1017592112", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1017592112", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0021-9045(72)90036-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020544127"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0024-3795(83)80026-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025181447"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0024-3795(83)80026-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025181447"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0168-9274(94)00037-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026412703"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01402562", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032748246", 
          "https://doi.org/10.1007/bf01402562"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01402562", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032748246", 
          "https://doi.org/10.1007/bf01402562"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-0-12-407475-0.50023-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042689043"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0001-8708(77)80029-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045231974"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0001-8708(77)80029-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045231974"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1090/s0002-9947-1954-0059635-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047041378"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/cnm.1630040318", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047965541"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/cnm.1630040318", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047965541"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1019105328973", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050247804", 
          "https://doi.org/10.1023/a:1019105328973"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-0-12-773050-9.50014-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050754974"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/0711020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062852177"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/0907058", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062855843"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2004", 
    "datePublishedReg": "2004-01-01", 
    "description": "It has been over fifty years since David M. Young\u2019s original work on the successive overrelaxation (SOR) methods. This fundamental method now appears in all textbooks containing an introductory discussion of iterative solution methods. (Most often the SOR method appears after a presentation of Jacobi iteration and Gauss-Seidel iteration and before the conjugate gradient iterative method.) We present a brief survey of some of the research of Professor David M. Young, together with his students and collaborators, on iterative methods for solving large sparse linear algebraic equations. This is not a complete survey but just a sampling of various papers with a focus on some of these publications. Dr. David M. Young\u2019s doctoral thesis [27] was accepted in 1950 by his supervising Professor Garrett Birkhoff of Harvard University and his paper [28] based this work appeared in 1954. This is one of the landmark contributions in modern numerical analysis. The red-black ordering for matrices is of great importance in parallel computing. Gene Golub has said: \u201cIt\u2019s almost as if David could see into the future!\u201d David Young celebrated his 80th birthday on October 20, 2003 (http://www.ma.utexas.edu/CNA/photos.html).", 
    "editor": [
      {
        "familyName": "Feistauer", 
        "givenName": "Miloslav", 
        "type": "Person"
      }, 
      {
        "familyName": "Dolej\u0161\u00ed", 
        "givenName": "V\u00edt", 
        "type": "Person"
      }, 
      {
        "familyName": "Knobloch", 
        "givenName": "Petr", 
        "type": "Person"
      }, 
      {
        "familyName": "Najzar", 
        "givenName": "Karel", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-642-18775-9_52", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-642-62288-5", 
        "978-3-642-18775-9"
      ], 
      "name": "Numerical Mathematics and Advanced Applications", 
      "type": "Book"
    }, 
    "name": "Celebrating Fifty Years of David M. Young\u2019s Successive Overrelaxation Method", 
    "pagination": "549-558", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1049971290"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-18775-9_52"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "ee0bf83ed0353a356b4bfbc56e35000167075b299ddf6997afc0f3d0bf66afe3"
        ]
      }
    ], 
    "publisher": {
      "location": "Berlin, Heidelberg", 
      "name": "Springer Berlin Heidelberg", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-18775-9_52", 
      "https://app.dimensions.ai/details/publication/pub.1049971290"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-16T08:56", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000369_0000000369/records_68953_00000001.jsonl", 
    "type": "Chapter", 
    "url": "https://link.springer.com/10.1007%2F978-3-642-18775-9_52"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-18775-9_52'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-18775-9_52'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-18775-9_52'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-18775-9_52'


 

This table displays all metadata directly associated to this object as RDF triples.

148 TRIPLES      23 PREDICATES      49 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-642-18775-9_52 schema:about anzsrc-for:01
2 anzsrc-for:0103
3 schema:author N2c18bbe764574b6a9d19dcc93f2fce5a
4 schema:citation sg:pub.10.1007/bf01386013
5 sg:pub.10.1007/bf01402562
6 sg:pub.10.1023/a:1019105328973
7 https://app.dimensions.ai/details/publication/pub.1017592112
8 https://doi.org/10.1002/cnm.1630040318
9 https://doi.org/10.1016/0021-9045(72)90036-6
10 https://doi.org/10.1016/0024-3795(80)90165-2
11 https://doi.org/10.1016/0024-3795(83)80026-3
12 https://doi.org/10.1016/0168-9274(94)00037-9
13 https://doi.org/10.1016/0377-0427(88)90347-0
14 https://doi.org/10.1016/0377-0427(96)00030-1
15 https://doi.org/10.1016/b978-0-12-407475-0.50023-1
16 https://doi.org/10.1016/b978-0-12-773050-9.50014-0
17 https://doi.org/10.1016/b978-1-4832-0078-1.50021-3
18 https://doi.org/10.1016/s0001-8708(77)80029-7
19 https://doi.org/10.1016/s0065-2458(08)60620-8
20 https://doi.org/10.1090/s0002-9947-1954-0059635-7
21 https://doi.org/10.1090/s0025-5718-1970-0281331-4
22 https://doi.org/10.1090/s0025-5718-1972-0311089-3
23 https://doi.org/10.1137/0711020
24 https://doi.org/10.1137/0907058
25 https://doi.org/10.1145/356004.356009
26 schema:datePublished 2004
27 schema:datePublishedReg 2004-01-01
28 schema:description It has been over fifty years since David M. Young’s original work on the successive overrelaxation (SOR) methods. This fundamental method now appears in all textbooks containing an introductory discussion of iterative solution methods. (Most often the SOR method appears after a presentation of Jacobi iteration and Gauss-Seidel iteration and before the conjugate gradient iterative method.) We present a brief survey of some of the research of Professor David M. Young, together with his students and collaborators, on iterative methods for solving large sparse linear algebraic equations. This is not a complete survey but just a sampling of various papers with a focus on some of these publications. Dr. David M. Young’s doctoral thesis [27] was accepted in 1950 by his supervising Professor Garrett Birkhoff of Harvard University and his paper [28] based this work appeared in 1954. This is one of the landmark contributions in modern numerical analysis. The red-black ordering for matrices is of great importance in parallel computing. Gene Golub has said: “It’s almost as if David could see into the future!” David Young celebrated his 80th birthday on October 20, 2003 (http://www.ma.utexas.edu/CNA/photos.html).
29 schema:editor N5c31e680e5a94e1681cc1206da62c2b9
30 schema:genre chapter
31 schema:inLanguage en
32 schema:isAccessibleForFree false
33 schema:isPartOf Nee2bca76bdb04cfa989ba48ce1cb3797
34 schema:name Celebrating Fifty Years of David M. Young’s Successive Overrelaxation Method
35 schema:pagination 549-558
36 schema:productId N29878c2965d2418ab7a5fc87074ac1fd
37 N2d26b17f19c54876b22182da8ca17f36
38 N83190fd77c7e45ca9a7745abf8e17a23
39 schema:publisher N347862804a994f4aa86c5e4ffc25a3ee
40 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049971290
41 https://doi.org/10.1007/978-3-642-18775-9_52
42 schema:sdDatePublished 2019-04-16T08:56
43 schema:sdLicense https://scigraph.springernature.com/explorer/license/
44 schema:sdPublisher Ncc6c44932c724442af12d11efa37baf4
45 schema:url https://link.springer.com/10.1007%2F978-3-642-18775-9_52
46 sgo:license sg:explorer/license/
47 sgo:sdDataset chapters
48 rdf:type schema:Chapter
49 N29878c2965d2418ab7a5fc87074ac1fd schema:name readcube_id
50 schema:value ee0bf83ed0353a356b4bfbc56e35000167075b299ddf6997afc0f3d0bf66afe3
51 rdf:type schema:PropertyValue
52 N2c18bbe764574b6a9d19dcc93f2fce5a rdf:first sg:person.013745557321.27
53 rdf:rest rdf:nil
54 N2d26b17f19c54876b22182da8ca17f36 schema:name dimensions_id
55 schema:value pub.1049971290
56 rdf:type schema:PropertyValue
57 N347862804a994f4aa86c5e4ffc25a3ee schema:location Berlin, Heidelberg
58 schema:name Springer Berlin Heidelberg
59 rdf:type schema:Organisation
60 N3dc3f2b6b82f4d17aa81c921d160d50d rdf:first N43e652aa66cd4b9d8a426fc5858b4b69
61 rdf:rest rdf:nil
62 N43e652aa66cd4b9d8a426fc5858b4b69 schema:familyName Najzar
63 schema:givenName Karel
64 rdf:type schema:Person
65 N5c31e680e5a94e1681cc1206da62c2b9 rdf:first Nd80103bff9374407900487ff6d41432d
66 rdf:rest Nab61faccd1c54fd2ba1b5b9e7f479864
67 N83190fd77c7e45ca9a7745abf8e17a23 schema:name doi
68 schema:value 10.1007/978-3-642-18775-9_52
69 rdf:type schema:PropertyValue
70 N8b80e0fae60444c59db41498c8cccc6b schema:familyName Knobloch
71 schema:givenName Petr
72 rdf:type schema:Person
73 Nab61faccd1c54fd2ba1b5b9e7f479864 rdf:first Nc9eb54f15bdf4d6db99844d39bead877
74 rdf:rest Nd602cda66e154f709c1198434d771be4
75 Nc9eb54f15bdf4d6db99844d39bead877 schema:familyName Dolejší
76 schema:givenName Vít
77 rdf:type schema:Person
78 Ncc6c44932c724442af12d11efa37baf4 schema:name Springer Nature - SN SciGraph project
79 rdf:type schema:Organization
80 Nd602cda66e154f709c1198434d771be4 rdf:first N8b80e0fae60444c59db41498c8cccc6b
81 rdf:rest N3dc3f2b6b82f4d17aa81c921d160d50d
82 Nd80103bff9374407900487ff6d41432d schema:familyName Feistauer
83 schema:givenName Miloslav
84 rdf:type schema:Person
85 Nee2bca76bdb04cfa989ba48ce1cb3797 schema:isbn 978-3-642-18775-9
86 978-3-642-62288-5
87 schema:name Numerical Mathematics and Advanced Applications
88 rdf:type schema:Book
89 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
90 schema:name Mathematical Sciences
91 rdf:type schema:DefinedTerm
92 anzsrc-for:0103 schema:inDefinedTermSet anzsrc-for:
93 schema:name Numerical and Computational Mathematics
94 rdf:type schema:DefinedTerm
95 sg:person.013745557321.27 schema:affiliation https://www.grid.ac/institutes/grid.89336.37
96 schema:familyName Kincaid
97 schema:givenName David R.
98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013745557321.27
99 rdf:type schema:Person
100 sg:pub.10.1007/bf01386013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002672967
101 https://doi.org/10.1007/bf01386013
102 rdf:type schema:CreativeWork
103 sg:pub.10.1007/bf01402562 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032748246
104 https://doi.org/10.1007/bf01402562
105 rdf:type schema:CreativeWork
106 sg:pub.10.1023/a:1019105328973 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050247804
107 https://doi.org/10.1023/a:1019105328973
108 rdf:type schema:CreativeWork
109 https://app.dimensions.ai/details/publication/pub.1017592112 schema:CreativeWork
110 https://doi.org/10.1002/cnm.1630040318 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047965541
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1016/0021-9045(72)90036-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020544127
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1016/0024-3795(80)90165-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017293764
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1016/0024-3795(83)80026-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025181447
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1016/0168-9274(94)00037-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026412703
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1016/0377-0427(88)90347-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014678091
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1016/0377-0427(96)00030-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017065682
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1016/b978-0-12-407475-0.50023-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042689043
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1016/b978-0-12-773050-9.50014-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050754974
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/b978-1-4832-0078-1.50021-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003495274
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/s0001-8708(77)80029-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045231974
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/s0065-2458(08)60620-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015190251
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1090/s0002-9947-1954-0059635-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047041378
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1090/s0025-5718-1970-0281331-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004224954
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1090/s0025-5718-1972-0311089-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014807608
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1137/0711020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062852177
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1137/0907058 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062855843
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1145/356004.356009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001863832
145 rdf:type schema:CreativeWork
146 https://www.grid.ac/institutes/grid.89336.37 schema:alternateName The University of Texas at Austin
147 schema:name Department of Computer Sciences, University of Texas at Austin, 78712, Austin, Texas, USA
148 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...