{"id":"https://openalex.org/W4387869713","doi":"https://doi.org/10.1109/mlsp55844.2023.10285931","title":"Generalised Active Learning With Annotation Quality Selection","display_name":"Generalised Active Learning With Annotation Quality Selection","publication_year":2023,"publication_date":"2023-09-17","ids":{"openalex":"https://openalex.org/W4387869713","doi":"https://doi.org/10.1109/mlsp55844.2023.10285931"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp55844.2023.10285931","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mlsp55844.2023.10285931","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},"type":"article","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/A5032339540","display_name":"Jakob Lindqvist","orcid":"https://orcid.org/0000-0003-2790-8775"},"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":true,"raw_author_name":"Jakob Lindqvist","raw_affiliation_strings":["Chalmers University of Technology,Dept. of Electrical Engineering,Gothenburg,Sweden","Dept. of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chalmers University of Technology,Dept. of Electrical Engineering,Gothenburg,Sweden","institution_ids":["https://openalex.org/I66862912"]},{"raw_affiliation_string":"Dept. of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068596594","display_name":"Amanda Olmin","orcid":"https://orcid.org/0000-0003-4209-874X"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Amanda Olmin","raw_affiliation_strings":["Linköping University,Dept. of Computer and Information Science,Linköping,Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Linköping University,Dept. of Computer and Information Science,Linköping,Sweden","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029413988","display_name":"Lennart Svensson","orcid":"https://orcid.org/0000-0003-0206-9186"},"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":"Lennart Svensson","raw_affiliation_strings":["Chalmers University of Technology,Dept. of Electrical Engineering,Gothenburg,Sweden","Dept. of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chalmers University of Technology,Dept. of Electrical Engineering,Gothenburg,Sweden","institution_ids":["https://openalex.org/I66862912"]},{"raw_affiliation_string":"Dept. of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045048407","display_name":"Fredrik Lindsten","orcid":"https://orcid.org/0000-0003-3749-5820"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Fredrik Lindsten","raw_affiliation_strings":["Linköping University,Dept. of Computer and Information Science,Linköping,Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Linköping University,Dept. of Computer and Information Science,Linköping,Sweden","institution_ids":["https://openalex.org/I102134673"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5032339540"],"corresponding_institution_ids":["https://openalex.org/I66862912"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1379969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"49","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9635000228881836,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9592999815940857,"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/annotation","display_name":"Annotation","score":0.8584345579147339},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7619357109069824},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.6530469655990601},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6067765355110168},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5565506815910339},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5544374585151672},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5483617186546326},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5199195742607117},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5087512135505676},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.45382794737815857},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.44018346071243286},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.42058008909225464},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3228253126144409},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15100380778312683},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.12916341423988342}],"concepts":[{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.8584345579147339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7619357109069824},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.6530469655990601},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6067765355110168},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5565506815910339},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5544374585151672},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5483617186546326},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5199195742607117},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5087512135505676},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.45382794737815857},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.44018346071243286},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.42058008909225464},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3228253126144409},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15100380778312683},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.12916341423988342},{"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/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mlsp55844.2023.10285931","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mlsp55844.2023.10285931","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:research.chalmers.se:538503","is_oa":false,"landing_page_url":"https://research.chalmers.se/en/publication/538503","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":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W138745945","https://openalex.org/W1553533669","https://openalex.org/W1638081485","https://openalex.org/W1686946872","https://openalex.org/W1872312298","https://openalex.org/W1995875735","https://openalex.org/W2094645502","https://openalex.org/W2136636278","https://openalex.org/W2354949621","https://openalex.org/W2740505281","https://openalex.org/W2997654229","https://openalex.org/W2997960807","https://openalex.org/W3094502228","https://openalex.org/W3107984262","https://openalex.org/W3157244600","https://openalex.org/W3159481202","https://openalex.org/W3175240777","https://openalex.org/W4296483387","https://openalex.org/W4365794481","https://openalex.org/W6605658577","https://openalex.org/W6633023078","https://openalex.org/W6639393196","https://openalex.org/W6785722797","https://openalex.org/W6810573224"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2358755282","https://openalex.org/W2625833328","https://openalex.org/W1533177136","https://openalex.org/W2544750528","https://openalex.org/W4378976585"],"abstract_inverted_index":{"In":[0],"this":[1,72],"paper":[2],"we":[3,48,75],"promote":[4],"a":[5,19,51,55,77,124,128],"general":[6],"formulation":[7,111],"of":[8,44,58,109],"active":[9],"learning":[10,64],"(AL),":[11],"wherein":[12],"the":[13,27,31,38,42,46,66,82,97,107],"typically":[14],"binary":[15],"decision":[16],"to":[17,25,41],"annotate":[18],"point":[20],"or":[21],"not":[22],"is":[23,123],"extended":[24],"selecting":[26,93],"qualities":[28,95],"with":[29,112],"which":[30,61],"points":[32],"should":[33],"be":[34],"annotated.":[35],"By":[36],"linking":[37],"annotation":[39,68,94],"quality":[40,53],"cost":[43],"acquiring":[45],"label,":[47],"can":[49],"trade":[50],"lower":[52],"for":[54,65,92,96,114,127],"larger":[56],"set":[57],"training":[59],"samples,":[60],"may":[62],"improve":[63],"same":[67],"cost.":[69],"To":[70],"investigate":[71],"AL":[73],"formulation,":[74],"introduce":[76],"concrete":[78],"criterion,":[79,129],"based":[80],"on":[81],"mutual":[83],"information":[84],"(MI)":[85],"between":[86],"model":[87],"parameters":[88],"and":[89,117,119],"noisy":[90],"labels,":[91],"entire":[98],"dataset,":[99],"before":[100],"any":[101],"labels":[102],"are":[103],"acquired.":[104],"We":[105],"illustrate":[106],"usefulness":[108],"our":[110],"examples":[113],"both":[115],"classification":[116],"regression":[118],"find":[120],"that":[121],"MI":[122],"good":[125],"candidate":[126],"but":[130],"its":[131,134],"complexity":[132],"limits":[133],"usefulness.":[135]},"counts_by_year":[],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2025-10-10T00:00:00"}