{"id":"https://openalex.org/W4224919570","doi":"https://doi.org/10.1109/icassp43922.2022.9747190","title":"Graph-Structured Sparse Regularization Via Convex Optimization","display_name":"Graph-Structured Sparse Regularization Via Convex Optimization","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4224919570","doi":"https://doi.org/10.1109/icassp43922.2022.9747190"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9747190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747190","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022358441","display_name":"Hiroki Kuroda","orcid":"https://orcid.org/0000-0002-8093-3219"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroki Kuroda","raw_affiliation_strings":["Ritsumeikan University,College of Information Science and Engineering","College of Information Science and Engineering, Ritsumeikan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ritsumeikan University,College of Information Science and Engineering","institution_ids":["https://openalex.org/I135768898"]},{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088737648","display_name":"Daichi Kitahara","orcid":"https://orcid.org/0000-0002-6365-4314"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daichi Kitahara","raw_affiliation_strings":["Ritsumeikan University,College of Information Science and Engineering","College of Information Science and Engineering, Ritsumeikan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ritsumeikan University,College of Information Science and Engineering","institution_ids":["https://openalex.org/I135768898"]},{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University","institution_ids":["https://openalex.org/I135768898"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I135768898"],"apc_list":null,"apc_paid":null,"fwci":0.6608,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74483044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"97","issue":null,"first_page":"5538","last_page":"5542"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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/T12676","display_name":"Machine Learning and ELM","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9836999773979187,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.5606966614723206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5172434449195862},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4813535809516907},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47024837136268616},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.45533838868141174},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.4510837495326996},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.4157279133796692},{"id":"https://openalex.org/keywords/convex-function","display_name":"Convex function","score":0.41194993257522583},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3913491368293762},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3591533899307251},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.338251531124115}],"concepts":[{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.5606966614723206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5172434449195862},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4813535809516907},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47024837136268616},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.45533838868141174},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.4510837495326996},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.4157279133796692},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.41194993257522583},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3913491368293762},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3591533899307251},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.338251531124115},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9747190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747190","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1826818071","https://openalex.org/W1838512412","https://openalex.org/W1946620893","https://openalex.org/W1970554427","https://openalex.org/W1970768703","https://openalex.org/W1981112674","https://openalex.org/W1989861837","https://openalex.org/W2005732955","https://openalex.org/W2016634354","https://openalex.org/W2051882509","https://openalex.org/W2079558799","https://openalex.org/W2092663520","https://openalex.org/W2094311431","https://openalex.org/W2098996169","https://openalex.org/W2107941784","https://openalex.org/W2108687351","https://openalex.org/W2114595593","https://openalex.org/W2135780853","https://openalex.org/W2138019504","https://openalex.org/W2169135699","https://openalex.org/W2180180824","https://openalex.org/W2528863944","https://openalex.org/W2575860482","https://openalex.org/W2583800550","https://openalex.org/W2594914074","https://openalex.org/W2799110708","https://openalex.org/W2921754629","https://openalex.org/W2943860135","https://openalex.org/W2963103936","https://openalex.org/W2963903482","https://openalex.org/W3000190659","https://openalex.org/W3004005148","https://openalex.org/W3099014882","https://openalex.org/W3100282982","https://openalex.org/W3105279496","https://openalex.org/W3160066882","https://openalex.org/W3163864994","https://openalex.org/W4245608944","https://openalex.org/W4375860094","https://openalex.org/W6638709362","https://openalex.org/W6676634215","https://openalex.org/W6732330048","https://openalex.org/W6762177823","https://openalex.org/W6795363321","https://openalex.org/W6806565602"],"related_works":["https://openalex.org/W2186864281","https://openalex.org/W4255427455","https://openalex.org/W1966025497","https://openalex.org/W68941528","https://openalex.org/W4206451355","https://openalex.org/W3153752017","https://openalex.org/W4387635768","https://openalex.org/W2187449906","https://openalex.org/W3011190762","https://openalex.org/W2962818859"],"abstract_inverted_index":{"In":[0],"this":[1,38],"paper,":[2],"we":[3,40],"present":[4],"a":[5,32,42,58],"novel":[6],"convex":[7,43,103],"method":[8,95],"for":[9],"the":[10,22,49,63,87,93,101],"graph-structured":[11,23,59],"sparse":[12,27],"recovery.":[13],"While":[14],"various":[15],"structured":[16,26],"sparsities":[17],"can":[18],"be":[19,31],"represented":[20],"as":[21,79],"sparsity,":[24],"graph-":[25],"recovery":[28,60],"remains":[29],"to":[30],"challenging":[33],"non-convex":[34],"problem.":[35],"To":[36],"solve":[37],"difficulty,":[39],"propose":[41],"penalty":[44],"function":[45],"which":[46,72],"automatically":[47],"identifies":[48],"relevant":[50],"subgraph":[51],"of":[52,75],"an":[53],"underlying":[54],"graph.":[55,88],"We":[56],"design":[57],"model":[61],"using":[62,105],"proposed":[64,94],"penalty,":[65],"and":[66,83],"develop":[67],"its":[68],"first-order":[69],"iterative":[70],"solver":[71],"consists":[73],"only":[74],"simple":[76],"operations":[77],"such":[78],"closed-form":[80],"proximity":[81],"operators":[82],"difference":[84],"operator":[85],"on":[86],"Numerical":[89],"experiments":[90],"show":[91],"that":[92],"has":[96],"better":[97],"estimation":[98],"accuracy":[99],"than":[100],"existing":[102],"regularizations":[104],"fixed":[106],"structures.":[107]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}