{"id":"https://openalex.org/W2554225867","doi":"https://doi.org/10.1109/ijcnn.2016.7727475","title":"A non-parametric approach for learning from crowds","display_name":"A non-parametric approach for learning from crowds","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2554225867","doi":"https://doi.org/10.1109/ijcnn.2016.7727475","mag":"2554225867"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727475","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727475","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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/A5101396518","display_name":"Jiayi Fu","orcid":"https://orcid.org/0009-0001-5011-2807"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayi Fu","raw_affiliation_strings":["USTC-Birmingham Joint Research Institute in Intelligent Computation and Its Applications (UBRI), University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"USTC-Birmingham Joint Research Institute in Intelligent Computation and Its Applications (UBRI), University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103101066","display_name":"Jinhong Zhong","orcid":"https://orcid.org/0000-0001-8401-0385"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhong Zhong","raw_affiliation_strings":["USTC-Birmingham Joint Research Institute in Intelligent Computation and Its Applications (UBRI), University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"USTC-Birmingham Joint Research Institute in Intelligent Computation and Its Applications (UBRI), University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100357493","display_name":"Yunfeng Liu","orcid":"https://orcid.org/0009-0001-2236-6615"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunfeng Liu","raw_affiliation_strings":["Department of Internal Search Platform Tencent Inc., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Internal Search Platform Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100344974","display_name":"Zhenyu Wang","orcid":"https://orcid.org/0000-0002-9815-8775"},"institutions":[{"id":"https://openalex.org/I4210150599","display_name":"Newford Research Institute of Advanced Technology","ror":"https://ror.org/03s2thv57","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210150599"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Wang","raw_affiliation_strings":["Newford Research Institute of Advanced Technology Wenzhou, Zhejiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Newford Research Institute of Advanced Technology Wenzhou, Zhejiang, China","institution_ids":["https://openalex.org/I4210150599"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021254405","display_name":"Ke Tang","orcid":"https://orcid.org/0000-0002-6236-2002"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Tang","raw_affiliation_strings":["USTC-Birmingham Joint Research Institute in Intelligent Computation and Its Applications (UBRI), University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"USTC-Birmingham Joint Research Institute in Intelligent Computation and Its Applications (UBRI), University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16414954,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2228","last_page":"2235"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.9948999881744385,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9751999974250793,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/crowds","display_name":"Crowds","score":0.929642379283905},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6916633248329163},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6782626509666443},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5611145496368408},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.535358190536499},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5134668946266174},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.4519299864768982},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.4502132534980774},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4360309839248657},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.4147895872592926},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.41084516048431396},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2211589217185974}],"concepts":[{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.929642379283905},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6916633248329163},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6782626509666443},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5611145496368408},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.535358190536499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5134668946266174},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.4519299864768982},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.4502132534980774},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4360309839248657},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.4147895872592926},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41084516048431396},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2211589217185974},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727475","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727475","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W9014458","https://openalex.org/W82775311","https://openalex.org/W1512098439","https://openalex.org/W1538131130","https://openalex.org/W1969557815","https://openalex.org/W1970381522","https://openalex.org/W2044507188","https://openalex.org/W2048741147","https://openalex.org/W2106568252","https://openalex.org/W2108598243","https://openalex.org/W2125943921","https://openalex.org/W2134305421","https://openalex.org/W2134974509","https://openalex.org/W2141708418","https://openalex.org/W2142518823","https://openalex.org/W2143104527","https://openalex.org/W2145111356","https://openalex.org/W2149273804","https://openalex.org/W2149489787","https://openalex.org/W2153848201","https://openalex.org/W2154096410","https://openalex.org/W2164124780","https://openalex.org/W2170989440","https://openalex.org/W2181558882","https://openalex.org/W2187444452","https://openalex.org/W2294591530","https://openalex.org/W2295145241","https://openalex.org/W2330857546","https://openalex.org/W2912727152","https://openalex.org/W2913879771","https://openalex.org/W3120740533","https://openalex.org/W3122078363","https://openalex.org/W4301899755","https://openalex.org/W6603353687","https://openalex.org/W6630527977","https://openalex.org/W6632100814","https://openalex.org/W6679959949","https://openalex.org/W6680957539","https://openalex.org/W6681931198","https://openalex.org/W6682171051","https://openalex.org/W6682471470","https://openalex.org/W6682707525","https://openalex.org/W6685936606","https://openalex.org/W6686975137","https://openalex.org/W6697072043","https://openalex.org/W6788247690"],"related_works":["https://openalex.org/W3032998312","https://openalex.org/W135177976","https://openalex.org/W4384486036","https://openalex.org/W1503094549","https://openalex.org/W2337920774","https://openalex.org/W4286908577","https://openalex.org/W2886410948","https://openalex.org/W2025875869","https://openalex.org/W4318823662","https://openalex.org/W3153752017"],"abstract_inverted_index":{"Learning":[0],"from":[1,31,78],"crowds,":[2],"which":[3],"the":[4,7,101,106],"labels":[5],"of":[6],"instances":[8],"are":[9],"collected":[10],"through":[11],"crowdsourcing":[12],"ways,":[13],"has":[14,82],"become":[15],"an":[16],"important":[17],"research":[18],"topic":[19],"recently.":[20],"Personal":[21],"Classifier":[22],"(PC)":[23],"approach":[24,28,40,81,96,108,116],"is":[25,48],"a":[26,49,69,83],"representative":[27],"for":[29,60,76],"learning":[30,77],"crowds":[32],"due":[33],"to":[34,100],"its":[35],"convex":[36,84],"optimization":[37,85],"formulation.":[38],"PC":[39,107],"makes":[41],"assumptions":[42,54,89],"about":[43,90],"parameters'":[44,91],"distribution,":[45],"thus":[46],"it":[47],"parametric":[50],"approach.":[51],"However,":[52],"these":[53],"may":[55],"not":[56],"always":[57],"hold,":[58],"especially":[59],"real-world":[61],"data":[62],"sets.":[63],"In":[64,93],"this":[65],"paper,":[66],"we":[67],"propose":[68],"new":[70],"non-parametric":[71],"approach,":[72,75],"called":[73],"NP":[74,80,95,115],"crowds.":[79],"formulation":[86],"but":[87],"without":[88],"distribution.":[92],"addition,":[94],"can":[97],"be":[98],"generalized":[99],"non-linear":[102],"case":[103],"directly,":[104],"while":[105],"does":[109],"not.":[110],"Experimental":[111],"studies":[112],"show":[113],"that":[114],"outperforms":[117],"other":[118],"two":[119],"compared":[120],"approaches.":[121]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}