On some accelerated optimization algorithms based on fixed point and linesearch techniques for convex minimization problems with applications View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2022-03-17

AUTHORS

Pornsak Yatakoat, Suthep Suantai, Adisak Hanjing

ABSTRACT

In this paper, we introduce and study a new accelerated algorithm based on forward–backward and SP-algorithm for solving a convex minimization problem of the sum of two convex and lower semicontinuous functions in a Hilbert space. Under some suitable control conditions, a weak convergence theorem of the proposed algorithm based on a fixed point is established. Moreover, we choose the stepsize of our algorithm which is independent on the Lipschitz constant of the gradient of the objective function by using a linesearch technique, and then a weak convergence result of the proposed algorithm is analyzed. As applications, we apply the proposed algorithm for solving the image restoration problems and compare its convergence behavior with other well-known algorithms in the literature. By our experiment, the algorithms have a higher efficiency than the others. More... »

PAGES

25

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13662-022-03698-5

DOI

http://dx.doi.org/10.1186/s13662-022-03698-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1146355840


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/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Mathematics, Faculty of Science, Nakhon Phanom University, Nakhon Phanom, Thailand", 
          "id": "http://www.grid.ac/institutes/grid.449231.9", 
          "name": [
            "Department of Mathematics, Faculty of Science, Nakhon Phanom University, Nakhon Phanom, Thailand"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yatakoat", 
        "givenName": "Pornsak", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Research Center in Mathematics and Applied Mathematics, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand", 
          "id": "http://www.grid.ac/institutes/grid.7132.7", 
          "name": [
            "Data Science Research Center, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand", 
            "Research Center in Mathematics and Applied Mathematics, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Suantai", 
        "givenName": "Suthep", 
        "id": "sg:person.010451575507.51", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010451575507.51"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Science and Mathematics, Rajamangala University of Technology Isan Surin Campus, Surin, Thailand", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Department of Science and Mathematics, Rajamangala University of Technology Isan Surin Campus, Surin, Thailand"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hanjing", 
        "givenName": "Adisak", 
        "id": "sg:person.013001310372.88", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013001310372.88"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/978-1-4419-9467-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044558790", 
          "https://doi.org/10.1007/978-1-4419-9467-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11117-012-0161-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042877620", 
          "https://doi.org/10.1007/s11117-012-0161-0"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2022-03-17", 
    "datePublishedReg": "2022-03-17", 
    "description": "In this paper, we introduce and study a new accelerated algorithm based on forward\u2013backward and SP-algorithm for solving a convex minimization problem of the sum of two convex and lower semicontinuous functions in a Hilbert space. Under some suitable control conditions, a weak convergence theorem of the proposed algorithm based on a fixed point is established. Moreover, we choose the stepsize of our algorithm which is independent on the Lipschitz constant of the gradient of the objective function by using a linesearch technique, and then a weak convergence result of the proposed algorithm is analyzed. As applications, we apply the proposed algorithm for solving the image restoration problems and compare its convergence behavior with other well-known algorithms in the literature. By our experiment, the algorithms have a higher efficiency than the others.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/s13662-022-03698-5", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1421475", 
        "issn": [
          "2731-4235"
        ], 
        "name": "Advances in Continuous and Discrete Models", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "2022"
      }
    ], 
    "keywords": [
      "convex minimization problem", 
      "linesearch technique", 
      "minimization problem", 
      "accelerated optimization algorithms", 
      "new accelerated algorithm", 
      "weak convergence theorem", 
      "weak convergence results", 
      "lower semicontinuous functions", 
      "suitable control conditions", 
      "image restoration problems", 
      "Hilbert space", 
      "convergence theorem", 
      "convergence results", 
      "convergence behavior", 
      "semicontinuous functions", 
      "optimization algorithm", 
      "objective function", 
      "accelerated algorithm", 
      "restoration problem", 
      "SP algorithm", 
      "algorithm", 
      "problem", 
      "stepsize", 
      "Lipschitz", 
      "theorem", 
      "convex", 
      "space", 
      "point", 
      "sum", 
      "applications", 
      "function", 
      "high efficiency", 
      "technique", 
      "gradient", 
      "efficiency", 
      "behavior", 
      "conditions", 
      "experiments", 
      "results", 
      "literature", 
      "control condition", 
      "paper"
    ], 
    "name": "On some accelerated optimization algorithms based on fixed point and linesearch techniques for convex minimization problems with applications", 
    "pagination": "25", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1146355840"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s13662-022-03698-5"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s13662-022-03698-5", 
      "https://app.dimensions.ai/details/publication/pub.1146355840"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-08-04T17:10", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220804/entities/gbq_results/article/article_929.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/s13662-022-03698-5"
  }
]
 

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.10.1186/s13662-022-03698-5'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13662-022-03698-5'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13662-022-03698-5'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13662-022-03698-5'


 

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

126 TRIPLES      21 PREDICATES      68 URIs      58 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s13662-022-03698-5 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author Nf37aaf299d644cd8a69310affd484bef
4 schema:citation sg:pub.10.1007/978-1-4419-9467-7
5 sg:pub.10.1007/s11117-012-0161-0
6 schema:datePublished 2022-03-17
7 schema:datePublishedReg 2022-03-17
8 schema:description In this paper, we introduce and study a new accelerated algorithm based on forward–backward and SP-algorithm for solving a convex minimization problem of the sum of two convex and lower semicontinuous functions in a Hilbert space. Under some suitable control conditions, a weak convergence theorem of the proposed algorithm based on a fixed point is established. Moreover, we choose the stepsize of our algorithm which is independent on the Lipschitz constant of the gradient of the objective function by using a linesearch technique, and then a weak convergence result of the proposed algorithm is analyzed. As applications, we apply the proposed algorithm for solving the image restoration problems and compare its convergence behavior with other well-known algorithms in the literature. By our experiment, the algorithms have a higher efficiency than the others.
9 schema:genre article
10 schema:isAccessibleForFree true
11 schema:isPartOf N64da890ecb944984b03258be5f284fd9
12 N6d524b9b526445a5acffb5c97abfe4c6
13 sg:journal.1421475
14 schema:keywords Hilbert space
15 Lipschitz
16 SP algorithm
17 accelerated algorithm
18 accelerated optimization algorithms
19 algorithm
20 applications
21 behavior
22 conditions
23 control condition
24 convergence behavior
25 convergence results
26 convergence theorem
27 convex
28 convex minimization problem
29 efficiency
30 experiments
31 function
32 gradient
33 high efficiency
34 image restoration problems
35 linesearch technique
36 literature
37 lower semicontinuous functions
38 minimization problem
39 new accelerated algorithm
40 objective function
41 optimization algorithm
42 paper
43 point
44 problem
45 restoration problem
46 results
47 semicontinuous functions
48 space
49 stepsize
50 suitable control conditions
51 sum
52 technique
53 theorem
54 weak convergence results
55 weak convergence theorem
56 schema:name On some accelerated optimization algorithms based on fixed point and linesearch techniques for convex minimization problems with applications
57 schema:pagination 25
58 schema:productId N326867b68f1445ac9c8be267877f6f7d
59 N3ede86256ee34ef9878f9e4225cb4cb9
60 schema:sameAs https://app.dimensions.ai/details/publication/pub.1146355840
61 https://doi.org/10.1186/s13662-022-03698-5
62 schema:sdDatePublished 2022-08-04T17:10
63 schema:sdLicense https://scigraph.springernature.com/explorer/license/
64 schema:sdPublisher N1013dc06328f43699efff85a6371b43c
65 schema:url https://doi.org/10.1186/s13662-022-03698-5
66 sgo:license sg:explorer/license/
67 sgo:sdDataset articles
68 rdf:type schema:ScholarlyArticle
69 N1013dc06328f43699efff85a6371b43c schema:name Springer Nature - SN SciGraph project
70 rdf:type schema:Organization
71 N326867b68f1445ac9c8be267877f6f7d schema:name dimensions_id
72 schema:value pub.1146355840
73 rdf:type schema:PropertyValue
74 N3ede86256ee34ef9878f9e4225cb4cb9 schema:name doi
75 schema:value 10.1186/s13662-022-03698-5
76 rdf:type schema:PropertyValue
77 N64da890ecb944984b03258be5f284fd9 schema:volumeNumber 2022
78 rdf:type schema:PublicationVolume
79 N6d524b9b526445a5acffb5c97abfe4c6 schema:issueNumber 1
80 rdf:type schema:PublicationIssue
81 N99a2f89d021f4ef7bd1c96d7bc600dbc rdf:first sg:person.013001310372.88
82 rdf:rest rdf:nil
83 Naa4d13efb3d74dc39b9fac94eedab135 rdf:first sg:person.010451575507.51
84 rdf:rest N99a2f89d021f4ef7bd1c96d7bc600dbc
85 Nad2e468e4cb84ebfb905fec42e4f18c2 schema:affiliation grid-institutes:grid.449231.9
86 schema:familyName Yatakoat
87 schema:givenName Pornsak
88 rdf:type schema:Person
89 Nf37aaf299d644cd8a69310affd484bef rdf:first Nad2e468e4cb84ebfb905fec42e4f18c2
90 rdf:rest Naa4d13efb3d74dc39b9fac94eedab135
91 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
92 schema:name Information and Computing Sciences
93 rdf:type schema:DefinedTerm
94 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
95 schema:name Artificial Intelligence and Image Processing
96 rdf:type schema:DefinedTerm
97 sg:journal.1421475 schema:issn 2731-4235
98 schema:name Advances in Continuous and Discrete Models
99 schema:publisher Springer Nature
100 rdf:type schema:Periodical
101 sg:person.010451575507.51 schema:affiliation grid-institutes:grid.7132.7
102 schema:familyName Suantai
103 schema:givenName Suthep
104 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010451575507.51
105 rdf:type schema:Person
106 sg:person.013001310372.88 schema:affiliation grid-institutes:None
107 schema:familyName Hanjing
108 schema:givenName Adisak
109 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013001310372.88
110 rdf:type schema:Person
111 sg:pub.10.1007/978-1-4419-9467-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044558790
112 https://doi.org/10.1007/978-1-4419-9467-7
113 rdf:type schema:CreativeWork
114 sg:pub.10.1007/s11117-012-0161-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042877620
115 https://doi.org/10.1007/s11117-012-0161-0
116 rdf:type schema:CreativeWork
117 grid-institutes:None schema:alternateName Department of Science and Mathematics, Rajamangala University of Technology Isan Surin Campus, Surin, Thailand
118 schema:name Department of Science and Mathematics, Rajamangala University of Technology Isan Surin Campus, Surin, Thailand
119 rdf:type schema:Organization
120 grid-institutes:grid.449231.9 schema:alternateName Department of Mathematics, Faculty of Science, Nakhon Phanom University, Nakhon Phanom, Thailand
121 schema:name Department of Mathematics, Faculty of Science, Nakhon Phanom University, Nakhon Phanom, Thailand
122 rdf:type schema:Organization
123 grid-institutes:grid.7132.7 schema:alternateName Research Center in Mathematics and Applied Mathematics, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
124 schema:name Data Science Research Center, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
125 Research Center in Mathematics and Applied Mathematics, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
126 rdf:type schema:Organization
 




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


...