{"id":"https://openalex.org/W3201933462","doi":"https://doi.org/10.3390/info12100392","title":"Understanding Collections of Related Datasets Using Dependent MMD Coresets","display_name":"Understanding Collections of Related Datasets Using Dependent MMD Coresets","publication_year":2021,"publication_date":"2021-09-23","ids":{"openalex":"https://openalex.org/W3201933462","doi":"https://doi.org/10.3390/info12100392","mag":"3201933462"},"language":"en","primary_location":{"id":"pmh:oai:mdpi.com:/2078-2489/12/10/392/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/info12100392","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Information; Volume 12; Issue 10; Pages: 392","raw_type":"Text"},"type":"article","indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://dx.doi.org/10.3390/info12100392","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090272445","display_name":"Sinead A. Williamson","orcid":"https://orcid.org/0000-0002-0572-0045"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sinead A. Williamson; Jette Henderson","raw_affiliation_strings":["Department of Statistics and Data Science, University of Texas at Austin, Austin, TX 78712, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Data Science, University of Texas at Austin, Austin, TX 78712, USA","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5090272445"],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":0.6999,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76677131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9994000196456909,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9962999820709229,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9958999752998352,"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/automatic-summarization","display_name":"Automatic summarization","score":0.8521144390106201},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6670487523078918},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6458734273910522},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38618433475494385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35125717520713806},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34919652342796326},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1543201208114624}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8521144390106201},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6670487523078918},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6458734273910522},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38618433475494385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35125717520713806},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34919652342796326},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1543201208114624},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:mdpi.com:/2078-2489/12/10/392/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/info12100392","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Information; Volume 12; Issue 10; Pages: 392","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:mdpi.com:/2078-2489/12/10/392/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/info12100392","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Information; Volume 12; Issue 10; Pages: 392","raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1605181314","https://openalex.org/W1965156122","https://openalex.org/W1967611219","https://openalex.org/W1981313592","https://openalex.org/W1981794758","https://openalex.org/W2064513326","https://openalex.org/W2084701050","https://openalex.org/W2099001231","https://openalex.org/W2100659887","https://openalex.org/W2101234009","https://openalex.org/W2122496402","https://openalex.org/W2126385963","https://openalex.org/W2135148528","https://openalex.org/W2143691488","https://openalex.org/W2145056192","https://openalex.org/W2194775991","https://openalex.org/W2212660284","https://openalex.org/W2328111639","https://openalex.org/W2396803061","https://openalex.org/W2804802441","https://openalex.org/W2892832844","https://openalex.org/W2964315040","https://openalex.org/W2978660978","https://openalex.org/W3000575602","https://openalex.org/W3003420231","https://openalex.org/W3030030520","https://openalex.org/W3032086959","https://openalex.org/W3102272852","https://openalex.org/W3134970617","https://openalex.org/W4206341000"],"related_works":["https://openalex.org/W2351187795","https://openalex.org/W2380641910","https://openalex.org/W2589098947","https://openalex.org/W2285613413","https://openalex.org/W2561691764","https://openalex.org/W2389846579","https://openalex.org/W2085627679","https://openalex.org/W1596799430","https://openalex.org/W2788732373","https://openalex.org/W4360986142"],"abstract_inverted_index":{"Understanding":[0],"how":[1,19],"two":[2],"datasets":[3,66,84],"differ":[4],"can":[5,36],"help":[6],"us":[7],"determine":[8],"whether":[9],"one":[10],"dataset":[11],"under-represents":[12],"certain":[13],"sub-populations,":[14],"and":[15,85],"provides":[16],"insights":[17],"into":[18],"well":[20],"models":[21],"will":[22],"generalize":[23],"across":[24,49],"datasets.":[25,50,91],"Representative":[26],"points":[27],"selected":[28],"by":[29],"a":[30,41,59],"maximum":[31],"mean":[32],"discrepancy":[33],"(MMD)":[34],"coreset":[35],"provide":[37],"interpretable":[38],"summaries":[39],"of":[40,65,70],"single":[42],"dataset,":[43],"but":[44],"are":[45,78],"not":[46],"easily":[47],"compared":[48],"In":[51],"this":[52],"paper,":[53],"we":[54],"introduce":[55],"dependent":[56,75],"MMD":[57,76],"coresets,":[58],"data":[60],"summarization":[61],"method":[62],"for":[63,80],"collections":[64],"that":[67,74],"facilitates":[68],"comparison":[69],"distributions.":[71],"We":[72],"show":[73],"coresets":[77],"useful":[79],"understanding":[81,86],"multiple":[82],"related":[83],"model":[87],"generalization":[88],"between":[89],"such":[90]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-10-10T00:00:00"}
