{"id":"https://openalex.org/W3191236559","doi":"https://doi.org/10.1007/s10618-021-00787-z","title":"BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent","display_name":"BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent","publication_year":2021,"publication_date":"2021-08-11","ids":{"openalex":"https://openalex.org/W3191236559","doi":"https://doi.org/10.1007/s10618-021-00787-z","mag":"3191236559"},"language":"en","primary_location":{"id":"doi:10.1007/s10618-021-00787-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-021-00787-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-021-00787-z.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10618-021-00787-z.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015456745","display_name":"Sibylle Hess","orcid":"https://orcid.org/0000-0002-2557-4604"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Sibylle Hess","raw_affiliation_strings":["Department of Mathematics and Computer Science, TU Eindhoven, 5600 MB Eindhoven, The Netherlands","Department of Mathematics and Computer Science, TU Eindhoven, 5600 MB, Eindhoven, The Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-2557-4604","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, TU Eindhoven, 5600 MB Eindhoven, The Netherlands","institution_ids":["https://openalex.org/I83019370"]},{"raw_affiliation_string":"Department of Mathematics and Computer Science, TU Eindhoven, 5600 MB, Eindhoven, The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059781945","display_name":"Gianvito Pio","orcid":"https://orcid.org/0000-0003-2520-3616"},"institutions":[{"id":"https://openalex.org/I4210152452","display_name":"Consorzio Interuniversitario Nazionale per l'Informatica","ror":"https://ror.org/03v8v5y65","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210152452"]},{"id":"https://openalex.org/I5561750","display_name":"University of Bari Aldo Moro","ror":"https://ror.org/027ynra39","country_code":"IT","type":"education","lineage":["https://openalex.org/I5561750"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Gianvito Pio","raw_affiliation_strings":["Big Data Lab, National Interuniversity Consortium for Informatics (CINI), Rome, Italy","Department of Computer Science, University of Bari Aldo Moro, Via Orabona, 4, Bari, Italy"],"raw_orcid":"https://orcid.org/0000-0003-2520-3616","affiliations":[{"raw_affiliation_string":"Big Data Lab, National Interuniversity Consortium for Informatics (CINI), Rome, Italy","institution_ids":["https://openalex.org/I4210152452"]},{"raw_affiliation_string":"Department of Computer Science, University of Bari Aldo Moro, Via Orabona, 4, Bari, Italy","institution_ids":["https://openalex.org/I5561750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064293224","display_name":"Michiel E. Hochstenbach","orcid":"https://orcid.org/0000-0002-9196-8257"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Michiel Hochstenbach","raw_affiliation_strings":["Department of Mathematics and Computer Science, TU Eindhoven, 5600 MB Eindhoven, The Netherlands","Department of Mathematics and Computer Science, TU Eindhoven, 5600 MB, Eindhoven, The Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-9196-8257","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, TU Eindhoven, 5600 MB Eindhoven, The Netherlands","institution_ids":["https://openalex.org/I83019370"]},{"raw_affiliation_string":"Department of Mathematics and Computer Science, TU Eindhoven, 5600 MB, Eindhoven, The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073750332","display_name":"Michelangelo Ceci","orcid":"https://orcid.org/0000-0002-6690-7583"},"institutions":[{"id":"https://openalex.org/I5561750","display_name":"University of Bari Aldo Moro","ror":"https://ror.org/027ynra39","country_code":"IT","type":"education","lineage":["https://openalex.org/I5561750"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Michelangelo Ceci","raw_affiliation_strings":["Department of Computer Science, University of Bari Aldo Moro, Via Orabona, 4, Bari, Italy"],"raw_orcid":"https://orcid.org/0000-0002-6690-7583","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Bari Aldo Moro, Via Orabona, 4, Bari, Italy","institution_ids":["https://openalex.org/I5561750"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015456745"],"corresponding_institution_ids":["https://openalex.org/I83019370"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.1651,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.8073648,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"35","issue":"6","first_page":"2542","last_page":"2576"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9973999857902527,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/biclustering","display_name":"Biclustering","score":0.867849588394165},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7229720950126648},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.696657121181488},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6460265517234802},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.5877949595451355},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5737154483795166},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.49253448843955994},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4836469888687134},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4746937155723572},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.42515790462493896},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42491668462753296},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3154010772705078},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.28290531039237976},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2053738534450531},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.20411533117294312},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.07363155484199524}],"concepts":[{"id":"https://openalex.org/C144817290","wikidata":"https://www.wikidata.org/wiki/Q2976575","display_name":"Biclustering","level":5,"score":0.867849588394165},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7229720950126648},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.696657121181488},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6460265517234802},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.5877949595451355},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5737154483795166},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.49253448843955994},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4836469888687134},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4746937155723572},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.42515790462493896},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42491668462753296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3154010772705078},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.28290531039237976},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2053738534450531},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.20411533117294312},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.07363155484199524},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s10618-021-00787-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-021-00787-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-021-00787-z.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},{"id":"pmh:oai:pure.tue.nl:openaire/0c9f8390-dea2-4cc8-b6f8-b3ab136eefac","is_oa":true,"landing_page_url":"https://research.tue.nl/en/publications/0c9f8390-dea2-4cc8-b6f8-b3ab136eefac","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Hess, S, Pio, G, Hochstenbach, M & Ceci, M 2021, 'BROCCOLI : overlapping and outlier-robust biclustering through proximal stochastic gradient descent', Data Mining and Knowledge Discovery, vol. 35, no. 6, pp. 2542-2576. https://doi.org/10.1007/s10618-021-00787-z","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:ricerca.uniba.it:11586/373021","is_oa":true,"landing_page_url":"https://hdl.handle.net/11586/373021","pdf_url":null,"source":{"id":"https://openalex.org/S4377196296","display_name":"CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I5561750","host_organization_name":"University of Bari Aldo Moro","host_organization_lineage":["https://openalex.org/I5561750"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:tue:oai:pure.tue.nl:publications/0c9f8390-dea2-4cc8-b6f8-b3ab136eefac","is_oa":true,"landing_page_url":"https://research.tue.nl/nl/publications/0c9f8390-dea2-4cc8-b6f8-b3ab136eefac","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Mining and Knowledge Discovery, 35(6), 2542 - 2576. Springer Open","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s10618-021-00787-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-021-00787-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-021-00787-z.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4396540860","display_name":null,"funder_award_id":"1852414-1-1","funder_id":"https://openalex.org/F4320321873","funder_display_name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca"}],"funders":[{"id":"https://openalex.org/F4320321873","display_name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca","ror":"https://ror.org/0166hxq48"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3191236559.pdf","grobid_xml":"https://content.openalex.org/works/W3191236559.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W23524565","https://openalex.org/W49942714","https://openalex.org/W189030447","https://openalex.org/W196542726","https://openalex.org/W1528144985","https://openalex.org/W1756265184","https://openalex.org/W1956126447","https://openalex.org/W1970039276","https://openalex.org/W1972221303","https://openalex.org/W1989174562","https://openalex.org/W1998011568","https://openalex.org/W2006053820","https://openalex.org/W2009784799","https://openalex.org/W2019564823","https://openalex.org/W2021993511","https://openalex.org/W2027982384","https://openalex.org/W2028335839","https://openalex.org/W2036328877","https://openalex.org/W2043545458","https://openalex.org/W2052819443","https://openalex.org/W2108119513","https://openalex.org/W2118712128","https://openalex.org/W2120895400","https://openalex.org/W2130158951","https://openalex.org/W2133576408","https://openalex.org/W2136897707","https://openalex.org/W2150593711","https://openalex.org/W2150930396","https://openalex.org/W2156935079","https://openalex.org/W2158312129","https://openalex.org/W2165766797","https://openalex.org/W2166098345","https://openalex.org/W2180590172","https://openalex.org/W2189591224","https://openalex.org/W2232845837","https://openalex.org/W2283587406","https://openalex.org/W2295538862","https://openalex.org/W2605058302","https://openalex.org/W2612556147","https://openalex.org/W2751449619","https://openalex.org/W2752190933","https://openalex.org/W2767766831","https://openalex.org/W2899474779","https://openalex.org/W2913535645","https://openalex.org/W2963655672","https://openalex.org/W2963794891","https://openalex.org/W2987283719","https://openalex.org/W3012618199","https://openalex.org/W3045720675","https://openalex.org/W3099831365","https://openalex.org/W3101661886","https://openalex.org/W3125164951","https://openalex.org/W4244393449"],"related_works":["https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W34555840","https://openalex.org/W2146544734"],"abstract_inverted_index":{"Abstract":[0],"Matrix":[1],"tri-factorization":[2],"subject":[3,59,119],"to":[4,50,60,71,99,102,120],"binary":[5,61,121],"constraints":[6],"is":[7,46,68,124],"a":[8,82,172,181],"versatile":[9],"and":[10,19,34,90,155,158,165,194],"powerful":[11,64],"framework":[12,65],"for":[13,26,56,116],"the":[14,29,39,42,51,57,63,75,96,127,145,178,185],"simultaneous":[15],"clustering":[16,30,196],"of":[17,31,41,53,66,77,132,171,175,184],"observations":[18,78],"features,":[20],"also":[21],"known":[22],"as":[23],"biclustering.":[24],"Applications":[25],"biclustering":[27,67],"encompass":[28],"high-dimensional":[32],"data":[33,36],"explorative":[35],"mining,":[37],"where":[38],"selection":[40],"most":[43],"important":[44],"features":[45],"relevant.":[47],"Unfortunately,":[48],"due":[49],"lack":[52],"suitable":[54],"methods":[55],"optimization":[58,114,130],"constraints,":[62,122],"typically":[69],"constrained":[70],"clusterings":[72],"which":[73,123],"partition":[74],"set":[76],"or":[79],"features.":[80],"As":[81],"result,":[83],"overlap":[84],"between":[85],"clusters":[86,187],"cannot":[87],"be":[88,100],"modelled":[89],"every":[91],"item,":[92],"even":[93,168],"outliers":[94],"in":[95,169,177],"data,":[97,157],"have":[98],"assigned":[101],"exactly":[103],"one":[104],"cluster.":[105],"In":[106],"this":[107],"paper":[108],"we":[109,138],"propose":[110],"Broccoli":[111,190],",":[112],"an":[113],"scheme":[115,131],"matrix":[117],"factorization":[118],"based":[125],"on":[126,144,152],"theoretically":[128],"well-founded":[129],"proximal":[133],"stochastic":[134],"gradient":[135],"descent.":[136],"Thereby,":[137],"do":[139],"not":[140],"impose":[141],"any":[142],"restrictions":[143],"obtained":[146],"clusters.":[147],"Our":[148],"experimental":[149],"evaluation,":[150],"performed":[151],"both":[153],"synthetic":[154],"real-world":[156],"against":[159],"6":[160],"competitor":[161],"algorithms,":[162],"show":[163],"reliable":[164],"competitive":[166],"performance,":[167],"presence":[170],"high":[173],"amount":[174],"noise":[176],"data.":[179],"Moreover,":[180],"qualitative":[182],"analysis":[183],"identified":[186],"shows":[188],"that":[189],"may":[191],"provide":[192],"meaningful":[193],"interpretable":[195],"structures.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6}],"updated_date":"2026-03-07T13:37:22.277990","created_date":"2025-10-10T00:00:00"}