{"id":"https://openalex.org/W3199885714","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534284","title":"One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes","display_name":"One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3199885714","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534284","mag":"3199885714"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534284","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534284","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5004940005","display_name":"Ilia Sucholutskv","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ilia Sucholutskv","raw_affiliation_strings":["University of Waterloo, Waterloo, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052031581","display_name":"Nam\u2010Hwui Kim","orcid":"https://orcid.org/0000-0001-7933-9012"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Nam-Hwui Kim","raw_affiliation_strings":["University of Waterloo, Waterloo, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007643370","display_name":"Ryan P. Browne","orcid":"https://orcid.org/0000-0003-4543-0218"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ryan P. Browne","raw_affiliation_strings":["University of Waterloo, Waterloo, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042203967","display_name":"Matthias Schonlau","orcid":"https://orcid.org/0009-0007-3651-9268"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Matthias Schonlau","raw_affiliation_strings":["University of Waterloo, Waterloo, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I151746483"],"apc_list":null,"apc_paid":null,"fwci":0.4396,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62317451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"571","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9976000189781189,"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":0.9976000189781189,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9976000189781189,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/shot","display_name":"Shot (pellet)","score":0.6503369212150574},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5429241061210632},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.5217786431312561},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3291884660720825},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14797550439834595},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.10076844692230225}],"concepts":[{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.6503369212150574},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5429241061210632},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.5217786431312561},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3291884660720825},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14797550439834595},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.10076844692230225},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534284","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534284","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W819631554","https://openalex.org/W1539563432","https://openalex.org/W1582081577","https://openalex.org/W1773652845","https://openalex.org/W1968541942","https://openalex.org/W2005150014","https://openalex.org/W2048997388","https://openalex.org/W2068514419","https://openalex.org/W2128262571","https://openalex.org/W2132862423","https://openalex.org/W2138457014","https://openalex.org/W2138798794","https://openalex.org/W2139246421","https://openalex.org/W2151537585","https://openalex.org/W2155319834","https://openalex.org/W2479531384","https://openalex.org/W2570764145","https://openalex.org/W2612467436","https://openalex.org/W2774918944","https://openalex.org/W2949071206","https://openalex.org/W2949979136","https://openalex.org/W2963809228","https://openalex.org/W2963902936","https://openalex.org/W2963966702","https://openalex.org/W2983647115","https://openalex.org/W3034942609","https://openalex.org/W3086607822","https://openalex.org/W3100055683","https://openalex.org/W3155042034","https://openalex.org/W4285719527","https://openalex.org/W4297825594","https://openalex.org/W4300885073","https://openalex.org/W4399585227","https://openalex.org/W6623175822","https://openalex.org/W6680412872","https://openalex.org/W6683152347","https://openalex.org/W6696497002","https://openalex.org/W6737232052","https://openalex.org/W6747231328","https://openalex.org/W6770130701","https://openalex.org/W6794192823"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2980279061","https://openalex.org/W2334685461","https://openalex.org/W2366718574","https://openalex.org/W2359774528"],"abstract_inverted_index":{"Increasingly":[0],"large":[1],"datasets":[2],"are":[3,113],"rapidly":[4],"driving":[5],"up":[6],"the":[7,34,56,71,117,122,128,153],"computational":[8,35],"costs":[9],"of":[10,22,37,51,74,119,155],"machine":[11],"learning.":[12],"Prototype":[13,131],"generation":[14],"methods":[15],"aim":[16],"to":[17,44,53,158],"create":[18],"a":[19,28,96,160],"small":[20,49],"set":[21],"synthetic":[23],"observations":[24],"that":[25,105,143],"accurately":[26,54],"represent":[27,55,159],"training":[29,58],"dataset":[30],"but":[31],"greatly":[32,151],"reduce":[33],"cost":[36],"learning":[38,68,75],"from":[39],"it.":[40],"Assigning":[41],"soft":[42],"labels":[43],"prototypes":[45,52,89,115,156],"can":[46],"allow":[47],"increasingly":[48],"sets":[50],"original":[57],"dataset.":[59],"Although":[60],"foundational":[61],"work":[62],"on":[63,137],"\u2018less":[64],"than":[65,78,116],"one\u2019":[66],"-shot":[67],"has":[69],"proven":[70],"theoretical":[72],"plausibility":[73],"with":[76,165],"fewer":[77,114],"one":[79],"observation":[80],"per":[81],"class,":[82],"developing":[83],"practical":[84],"algorithms":[85],"for":[86,100],"generating":[87,101],"such":[88],"remains":[90],"an":[91],"unexplored":[92],"territory.":[93],"We":[94,141],"propose":[95,127],"novel,":[97],"modular":[98],"method":[99,145],"soft-label":[102],"prototypical":[103,139],"lines":[104],"still":[106],"maintains":[107,146],"representational":[108],"accuracy":[109,149],"even":[110,162],"when":[111,163],"there":[112],"number":[118,154],"classes":[120],"in":[121],"data.":[123,170],"In":[124],"addition,":[125],"we":[126],"Hierarchical":[129],"Soft-Label":[130],"k-Nearest":[132],"Neighbor":[133],"classification":[134,148],"algorithm":[135],"based":[136],"these":[138],"lines.":[140],"show":[142],"our":[144],"high":[147],"while":[150],"reducing":[152],"required":[157],"dataset,":[161],"working":[164],"severely":[166],"imbalanced":[167],"and":[168],"difficult":[169],"Our":[171],"code":[172],"is":[173],"available":[174],"at":[175],"https://github.com/ilia10000/SLkNN.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2021-09-27T00:00:00"}