{"id":"https://openalex.org/W4400229030","doi":"https://doi.org/10.1080/00401706.2024.2374554","title":"Active Sampling: A Machine-Learning-Assisted Framework for Finite Population Inference with Optimal Subsamples","display_name":"Active Sampling: A Machine-Learning-Assisted Framework for Finite Population Inference with Optimal Subsamples","publication_year":2024,"publication_date":"2024-07-02","ids":{"openalex":"https://openalex.org/W4400229030","doi":"https://doi.org/10.1080/00401706.2024.2374554"},"language":"en","primary_location":{"id":"doi:10.1080/00401706.2024.2374554","is_oa":true,"landing_page_url":"https://doi.org/10.1080/00401706.2024.2374554","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1080/00401706.2024.2374554","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058205024","display_name":"Henrik Imberg","orcid":"https://orcid.org/0000-0001-9447-663X"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]},{"id":"https://openalex.org/I881427289","display_name":"University of Gothenburg","ror":"https://ror.org/01tm6cn81","country_code":"SE","type":"education","lineage":["https://openalex.org/I881427289"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Henrik Imberg","raw_affiliation_strings":["Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg","Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg","institution_ids":["https://openalex.org/I66862912","https://openalex.org/I881427289"]},{"raw_affiliation_string":"Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912","https://openalex.org/I881427289"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060055410","display_name":"Xiaomi Yang","orcid":"https://orcid.org/0000-0003-1641-9634"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Xiaomi Yang","raw_affiliation_strings":["Division of Vehicle Safety, Chalmers University of Technology","Division of Vehicle Safety, Chalmers University of Technology, Gothenburg, Sweden"],"affiliations":[{"raw_affiliation_string":"Division of Vehicle Safety, Chalmers University of Technology","institution_ids":["https://openalex.org/I66862912"]},{"raw_affiliation_string":"Division of Vehicle Safety, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004959786","display_name":"Carol Flannagan","orcid":"https://orcid.org/0000-0001-8484-4187"},"institutions":[{"id":"https://openalex.org/I1311636904","display_name":"Michigan Department of Transportation","ror":"https://ror.org/01kae7563","country_code":"US","type":"government","lineage":["https://openalex.org/I1311636904"]},{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]},{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE","US"],"is_corresponding":false,"raw_author_name":"Carol Flannagan","raw_affiliation_strings":["Division of Vehicle Safety, Chalmers University of Technology","University of Michigan Transportation Research Institute","University of Michigan Transportation Research Institute, Ann Arbor, Michigan, USA","University of Michigan Transportation Research Institute, Division of Vehicle Safety, Chalmers University of Technology"],"affiliations":[{"raw_affiliation_string":"Division of Vehicle Safety, Chalmers University of Technology","institution_ids":["https://openalex.org/I66862912"]},{"raw_affiliation_string":"University of Michigan Transportation Research Institute","institution_ids":["https://openalex.org/I1311636904","https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Michigan Transportation Research Institute, Ann Arbor, Michigan, USA","institution_ids":["https://openalex.org/I1311636904","https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Michigan Transportation Research Institute, Division of Vehicle Safety, Chalmers University of Technology","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021204321","display_name":"Jonas B\u00e4rgman","orcid":"https://orcid.org/0000-0002-3578-2546"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Jonas B\u00e4rgman","raw_affiliation_strings":["Division of Vehicle Safety, Chalmers University of Technology","Division of Vehicle Safety, Chalmers University of Technology, Gothenburg, Sweden"],"affiliations":[{"raw_affiliation_string":"Division of Vehicle Safety, Chalmers University of Technology","institution_ids":["https://openalex.org/I66862912"]},{"raw_affiliation_string":"Division of Vehicle Safety, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5058205024"],"corresponding_institution_ids":["https://openalex.org/I66862912","https://openalex.org/I881427289"],"apc_list":null,"apc_paid":null,"fwci":1.0425,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.79980726,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"67","issue":"1","first_page":"46","last_page":"57"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9988999962806702,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9988999962806702,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9812999963760376,"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/inference","display_name":"Inference","score":0.7115516662597656},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5785583853721619},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5527960062026978},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.524990439414978},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5133635401725769},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.44213634729385376},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42798590660095215},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38075941801071167},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.32330960035324097},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31992077827453613},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.07623016834259033}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7115516662597656},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5785583853721619},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5527960062026978},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.524990439414978},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5133635401725769},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.44213634729385376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42798590660095215},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38075941801071167},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.32330960035324097},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31992077827453613},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.07623016834259033},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/00401706.2024.2374554","is_oa":true,"landing_page_url":"https://doi.org/10.1080/00401706.2024.2374554","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"},{"id":"pmh:oai:research.chalmers.se:543038","is_oa":false,"landing_page_url":"https://research.chalmers.se/en/publication/b5d1d89a-2bee-465f-adcc-e686a4fdfeb9","pdf_url":null,"source":{"id":"https://openalex.org/S4306402469","display_name":"Chalmers Research (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"doi:10.1080/00401706.2024.2374554","is_oa":true,"landing_page_url":"https://doi.org/10.1080/00401706.2024.2374554","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W1825523523","https://openalex.org/W1986050895","https://openalex.org/W2001331635","https://openalex.org/W2003381716","https://openalex.org/W2015399216","https://openalex.org/W2019491306","https://openalex.org/W2022637125","https://openalex.org/W2029685080","https://openalex.org/W2045067839","https://openalex.org/W2063986268","https://openalex.org/W2077563060","https://openalex.org/W2109033052","https://openalex.org/W2115305054","https://openalex.org/W2116780995","https://openalex.org/W2117897510","https://openalex.org/W2125275885","https://openalex.org/W2167595980","https://openalex.org/W2180998347","https://openalex.org/W2253901153","https://openalex.org/W2295598076","https://openalex.org/W2582743722","https://openalex.org/W2596535828","https://openalex.org/W2607420770","https://openalex.org/W2613889334","https://openalex.org/W2767824335","https://openalex.org/W2904100967","https://openalex.org/W2904739162","https://openalex.org/W2911964244","https://openalex.org/W2916338083","https://openalex.org/W2936646822","https://openalex.org/W2943847575","https://openalex.org/W2955073550","https://openalex.org/W2955312852","https://openalex.org/W2963508324","https://openalex.org/W2963726264","https://openalex.org/W3007063426","https://openalex.org/W3028903392","https://openalex.org/W3034724369","https://openalex.org/W3037232215","https://openalex.org/W3037644189","https://openalex.org/W3043888703","https://openalex.org/W3080841735","https://openalex.org/W3092441238","https://openalex.org/W3097162844","https://openalex.org/W3102353912","https://openalex.org/W3111352075","https://openalex.org/W3119881326","https://openalex.org/W3127647470","https://openalex.org/W3156216502","https://openalex.org/W3200761280","https://openalex.org/W3205626500","https://openalex.org/W4200570147","https://openalex.org/W4205536138","https://openalex.org/W4206070193","https://openalex.org/W4206410470","https://openalex.org/W4206723194","https://openalex.org/W4229739412","https://openalex.org/W4233471163","https://openalex.org/W4249743219","https://openalex.org/W4281770813","https://openalex.org/W4288050399","https://openalex.org/W4296847028","https://openalex.org/W4298872162","https://openalex.org/W4300000261","https://openalex.org/W4318621628","https://openalex.org/W4385191393","https://openalex.org/W4387743165","https://openalex.org/W6677280552","https://openalex.org/W6779967550","https://openalex.org/W6849387969"],"related_works":["https://openalex.org/W2055243143","https://openalex.org/W4321636575","https://openalex.org/W1986418932","https://openalex.org/W137830373","https://openalex.org/W3000984192","https://openalex.org/W2103073163","https://openalex.org/W4286952477","https://openalex.org/W4321348134","https://openalex.org/W4387929287","https://openalex.org/W1981934814"],"abstract_inverted_index":{"Data":[0],"subsampling":[1],"has":[2],"become":[3],"widely":[4],"recognized":[5],"as":[6],"a":[7],"tool":[8],"to":[9,21,85],"overcome":[10],"computational":[11],"and":[12,36,50],"economic":[13],"bottlenecks":[14],"in":[15],"analyzing":[16],"massive":[17],"datasets.":[18],"We":[19,40],"contribute":[20],"the":[22],"development":[23],"of":[24,29,74],"adaptive":[25,37],"design":[26],"for":[27],"estimation":[28,49],"finite":[30],"population":[31],"characteristics,":[32],"using":[33],"active":[34,43],"learning":[35,59],"importance":[38],"sampling.":[39],"propose":[41],"an":[42],"sampling":[44,87],"strategy":[45],"that":[46],"iterates":[47],"between":[48],"data":[51],"collection":[52],"with":[53],"optimal":[54],"subsamples,":[55],"guided":[56],"by":[57],"machine":[58],"predictions":[60],"on":[61,69],"yet":[62],"unseen":[63],"data.":[64],"The":[65],"method":[66],"is":[67],"illustrated":[68],"virtual":[70],"simulation-based":[71],"safety":[72],"assessment":[73],"advanced":[75],"driver":[76],"assistance":[77],"systems.":[78],"Substantial":[79],"performance":[80],"improvements":[81],"are":[82],"demonstrated":[83],"compared":[84],"traditional":[86],"methods.":[88]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}