{"id":"https://openalex.org/W3089475690","doi":"https://doi.org/10.1007/s11590-021-01762-9","title":"A block coordinate descent method for sensor network localization","display_name":"A block coordinate descent method for sensor network localization","publication_year":2021,"publication_date":"2021-06-07","ids":{"openalex":"https://openalex.org/W3089475690","doi":"https://doi.org/10.1007/s11590-021-01762-9","mag":"3089475690"},"language":"en","primary_location":{"id":"doi:10.1007/s11590-021-01762-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11590-021-01762-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11590-021-01762-9.pdf","source":{"id":"https://openalex.org/S12647387","display_name":"Optimization Letters","issn_l":"1862-4472","issn":["1862-4472","1862-4480"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Optimization Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11590-021-01762-9.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Mitsuhiro Nishijima","orcid":"https://orcid.org/0000-0003-4871-9156"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Mitsuhiro Nishijima","raw_affiliation_strings":["Department of Industrial Engineering and Economics, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan"],"raw_orcid":"https://orcid.org/0000-0003-4871-9156","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering and Economics, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":null,"display_name":"Kazuhide Nakata","orcid":"https://orcid.org/0000-0002-5479-100X"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuhide Nakata","raw_affiliation_strings":["Department of Industrial Engineering and Economics, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5479-100X","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering and Economics, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":0.4067,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.58933017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"16","issue":"3","first_page":"1051","last_page":"1071"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.5536999702453613,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.5536999702453613,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.1264999955892563,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10963","display_name":"Advanced Optimization Algorithms Research","score":0.04450000077486038,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/coordinate-descent","display_name":"Coordinate descent","score":0.9093999862670898},{"id":"https://openalex.org/keywords/semidefinite-programming","display_name":"Semidefinite programming","score":0.6926000118255615},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5236999988555908},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5163999795913696},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4934999942779541},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4837999939918518},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.47859999537467957},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.43470001220703125},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4316999912261963}],"concepts":[{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.9093999862670898},{"id":"https://openalex.org/C101901036","wikidata":"https://www.wikidata.org/wiki/Q2269096","display_name":"Semidefinite programming","level":2,"score":0.6926000118255615},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5327000021934509},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5248000025749207},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5236999988555908},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5163999795913696},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4934999942779541},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4837999939918518},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.47859999537467957},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.476500004529953},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.43470001220703125},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C85817219","wikidata":"https://www.wikidata.org/wiki/Q884772","display_name":"Block matrix","level":3,"score":0.41429999470710754},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3727000057697296},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.36800000071525574},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.34610000252723694},{"id":"https://openalex.org/C189237950","wikidata":"https://www.wikidata.org/wiki/Q2500758","display_name":"Stationary point","level":2,"score":0.33880001306533813},{"id":"https://openalex.org/C2776637919","wikidata":"https://www.wikidata.org/wiki/Q624380","display_name":"Descent (aeronautics)","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C116149140","wikidata":"https://www.wikidata.org/wiki/Q2070951","display_name":"Descent direction","level":4,"score":0.32749998569488525},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.32350000739097595},{"id":"https://openalex.org/C80551277","wikidata":"https://www.wikidata.org/wiki/Q11210","display_name":"Coordinate system","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C6180225","wikidata":"https://www.wikidata.org/wiki/Q3411771","display_name":"Penalty method","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C49712288","wikidata":"https://www.wikidata.org/wiki/Q77601250","display_name":"Positive-definite matrix","level":3,"score":0.27720001339912415},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.2689000070095062},{"id":"https://openalex.org/C55660270","wikidata":"https://www.wikidata.org/wiki/Q5164377","display_name":"Constrained optimization","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11590-021-01762-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11590-021-01762-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11590-021-01762-9.pdf","source":{"id":"https://openalex.org/S12647387","display_name":"Optimization Letters","issn_l":"1862-4472","issn":["1862-4472","1862-4480"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Optimization Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2010.01287","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.01287","pdf_url":"https://arxiv.org/pdf/2010.01287","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1007/s11590-021-01762-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11590-021-01762-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11590-021-01762-9.pdf","source":{"id":"https://openalex.org/S12647387","display_name":"Optimization Letters","issn_l":"1862-4472","issn":["1862-4472","1862-4480"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Optimization Letters","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1578126719","display_name":null,"funder_award_id":"JP20H02385","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3089475690.pdf","grobid_xml":"https://content.openalex.org/works/W3089475690.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W18819324","https://openalex.org/W1964590153","https://openalex.org/W1968154520","https://openalex.org/W1983766376","https://openalex.org/W2000769684","https://openalex.org/W2009271970","https://openalex.org/W2013850411","https://openalex.org/W2025617394","https://openalex.org/W2049444669","https://openalex.org/W2065569293","https://openalex.org/W2070503827","https://openalex.org/W2086953401","https://openalex.org/W2143075842","https://openalex.org/W2146281661","https://openalex.org/W2156865565","https://openalex.org/W2549541904","https://openalex.org/W2955343101","https://openalex.org/W2972449988","https://openalex.org/W3138835833","https://openalex.org/W4236366895","https://openalex.org/W4292363360"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"The":[1],"problem":[2,15],"of":[3,42,54,92,129,138],"sensor":[4,172],"network":[5],"localization":[6],"(SNL)":[7],"can":[8,111],"be":[9,113],"formulated":[10],"as":[11,69],"a":[12,17,22,32,40,59,126,136],"semidefinite":[13,33],"programming":[14],"with":[16,35,58,116],"rank":[18,37,166],"constraint.":[19],"We":[20,30,133],"propose":[21],"new":[23],"method":[24,95,110,162],"for":[25,142],"solving":[26],"such":[27],"SNL":[28,68],"problems.":[29],"factorize":[31],"matrix":[34],"the":[36,46,52,55,63,79,93,106,117,130,139,144,149,160,165,180,185],"constraint":[38,167],"into":[39],"product":[41],"two":[43,56,145],"matrices":[44,146],"via":[45],"Burer\u2013Monteiro":[47],"factorization.":[48],"Then,":[49],"we":[50,77,87],"add":[51],"difference":[53],"matrices,":[57],"penalty":[60,140],"parameter,":[61],"to":[62,75,125],"objective":[64,131],"function,":[65],"thereby":[66],"reformulating":[67],"an":[70],"unconstrained":[71],"multiconvex":[72],"optimization":[73],"problem,":[74],"which":[76,143],"apply":[78],"block":[80,107],"coordinate":[81,108],"descent":[82,109],"method.":[83],"In":[84],"this":[85],"paper,":[86],"also":[88,112,134],"provide":[89],"theoretical":[90],"analyses":[91],"proposed":[94,122,161],"and":[96,168],"show":[97],"that":[98,101,159,169],"each":[99],"subproblem":[100],"is":[102],"solved":[103,114],"sequentially":[104],"by":[105,120],"analytically,":[115],"sequence":[118],"generated":[119],"our":[121],"algorithm":[123],"converging":[124],"stationary":[127],"point":[128],"function.":[132],"give":[135],"range":[137],"parameter":[141],"used":[147],"in":[148],"factorization":[150],"agree":[151],"at":[152],"any":[153],"accumulation":[154],"point.":[155],"Numerical":[156],"experiments":[157],"confirm":[158],"does":[163],"inherit":[164],"it":[170],"estimates":[171],"positions":[173],"faster":[174],"than":[175],"other":[176],"methods":[177],"without":[178],"sacrificing":[179],"estimation":[181],"accuracy,":[182],"especially":[183],"when":[184],"measured":[186],"distances":[187],"contain":[188],"errors.":[189]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2020-10-08T00:00:00"}
