{"id":"https://openalex.org/W2516027932","doi":"https://doi.org/10.1145/2971648.2971701","title":"Learning from less for better","display_name":"Learning from less for better","publication_year":2016,"publication_date":"2016-09-09","ids":{"openalex":"https://openalex.org/W2516027932","doi":"https://doi.org/10.1145/2971648.2971701","mag":"2516027932"},"language":"en","primary_location":{"id":"doi:10.1145/2971648.2971701","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2971648.2971701","pdf_url":null,"source":null,"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","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/A5052731721","display_name":"Lina Yao","orcid":"https://orcid.org/0000-0002-4149-839X"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Lina Yao","raw_affiliation_strings":["UNSW Australia, NSW 2052, Australia"],"affiliations":[{"raw_affiliation_string":"UNSW Australia, NSW 2052, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003222421","display_name":"Feiping Nie","orcid":"https://orcid.org/0000-0002-0871-6519"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feiping Nie","raw_affiliation_strings":["Northwestern Polytechnical University, Shaanxi 710072, China"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Shaanxi 710072, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080744092","display_name":"Quan Z. Sheng","orcid":"https://orcid.org/0000-0002-3326-4147"},"institutions":[{"id":"https://openalex.org/I5681781","display_name":"University of Adelaide","ror":"https://ror.org/00892tw58","country_code":"AU","type":"education","lineage":["https://openalex.org/I5681781"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Quan Z. Sheng","raw_affiliation_strings":["The University of Adelaide, Adelaide, SA 5005, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Adelaide, Adelaide, SA 5005, Australia","institution_ids":["https://openalex.org/I5681781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054698524","display_name":"Tao Gu","orcid":"https://orcid.org/0000-0002-1350-6639"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tao Gu","raw_affiliation_strings":["RMIT University, Melbourne, VIC 3000, Australia"],"affiliations":[{"raw_affiliation_string":"RMIT University, Melbourne, VIC 3000, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100372201","display_name":"Xue Li","orcid":"https://orcid.org/0000-0002-4515-6792"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xue Li","raw_affiliation_strings":["The University of Queensland, QLD 4072, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Queensland, QLD 4072, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100350745","display_name":"Sen Wang","orcid":"https://orcid.org/0000-0002-5414-8276"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sen Wang","raw_affiliation_strings":["Griffith University, QLD 4111, Australia"],"affiliations":[{"raw_affiliation_string":"Griffith University, QLD 4111, Australia","institution_ids":["https://openalex.org/I11701301"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5052731721"],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":4.6761,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.9675936,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9925000071525574,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7287903428077698},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7286475896835327},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7011546492576599},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6555283069610596},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.6053876280784607},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5540657043457031},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5259654521942139},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5085247755050659},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.5070986747741699},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4865955114364624},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.48208457231521606},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.4781547486782074},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4641987085342407},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.379635751247406},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3348523676395416},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20548829436302185}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7287903428077698},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7286475896835327},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7011546492576599},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6555283069610596},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.6053876280784607},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5540657043457031},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5259654521942139},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5085247755050659},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.5070986747741699},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4865955114364624},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.48208457231521606},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4781547486782074},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4641987085342407},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.379635751247406},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3348523676395416},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20548829436302185},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/2971648.2971701","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2971648.2971701","pdf_url":null,"source":null,"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:alma.61RMIT_INST:11247112850001341","is_oa":false,"landing_page_url":"http://doi.org/10.1145/2971648.2971701","pdf_url":null,"source":{"id":"https://openalex.org/S4306402074","display_name":"RMIT Research Repository (RMIT University Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I82951845","host_organization_name":"RMIT University","host_organization_lineage":["https://openalex.org/I82951845"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:digital.library.adelaide.edu.au:2440/110616","is_oa":false,"landing_page_url":"http://hdl.handle.net/2440/110616","pdf_url":null,"source":{"id":"https://openalex.org/S4306401835","display_name":"Adelaide Research & Scholarship (AR&S) (University of Adelaide)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I5681781","host_organization_name":"The University of Adelaide","host_organization_lineage":["https://openalex.org/I5681781"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://dx.doi.org/10.1145/2971648.2971701","raw_type":"Conference paper"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/123941","is_oa":false,"landing_page_url":"http://hdl.handle.net/10072/123941","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"id":"https://metadata.un.org/sdg/1","display_name":"No poverty"}],"awards":[{"id":"https://openalex.org/G8414968054","display_name":null,"funder_award_id":"DP130104614, DE160100509","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W98188630","https://openalex.org/W134960717","https://openalex.org/W1497385253","https://openalex.org/W1501073070","https://openalex.org/W1527439439","https://openalex.org/W1567149586","https://openalex.org/W1606626619","https://openalex.org/W1969307352","https://openalex.org/W1988412055","https://openalex.org/W2009501510","https://openalex.org/W2015260841","https://openalex.org/W2015295583","https://openalex.org/W2015372742","https://openalex.org/W2017634428","https://openalex.org/W2023302299","https://openalex.org/W2025341678","https://openalex.org/W2048679005","https://openalex.org/W2059732136","https://openalex.org/W2073539200","https://openalex.org/W2087215247","https://openalex.org/W2101785535","https://openalex.org/W2104290444","https://openalex.org/W2105046342","https://openalex.org/W2105414191","https://openalex.org/W2106981652","https://openalex.org/W2112229395","https://openalex.org/W2117614111","https://openalex.org/W2124823771","https://openalex.org/W2127498532","https://openalex.org/W2130903752","https://openalex.org/W2131709365","https://openalex.org/W2136010533","https://openalex.org/W2139823104","https://openalex.org/W2141253759","https://openalex.org/W2143364815","https://openalex.org/W2145343602","https://openalex.org/W2146489051","https://openalex.org/W2154455818","https://openalex.org/W2159613676","https://openalex.org/W2171837816","https://openalex.org/W2241720604","https://openalex.org/W2247607085","https://openalex.org/W2273937221","https://openalex.org/W2295626104","https://openalex.org/W2595142274","https://openalex.org/W2798909945","https://openalex.org/W2997701990","https://openalex.org/W4300644646","https://openalex.org/W6604091132"],"related_works":["https://openalex.org/W4312414840","https://openalex.org/W2794908468","https://openalex.org/W4206276646","https://openalex.org/W2943467239","https://openalex.org/W1571801203","https://openalex.org/W2610740816","https://openalex.org/W101422005","https://openalex.org/W192740413","https://openalex.org/W3004135598","https://openalex.org/W2168489430"],"abstract_inverted_index":{"Despite":[0],"the":[1,6,13,39,54,79,90,101],"active":[2],"research":[3],"into,":[4],"and":[5,30,89,107,120,130],"development":[7],"of,":[8],"human":[9],"activity":[10,41,74],"recognition":[11,75,132],"over":[12],"decades,":[14],"existing":[15],"techniques":[16],"still":[17],"have":[18],"several":[19],"limitations,":[20],"in":[21,45,67,126],"particular,":[22],"poor":[23],"performance":[24],"due":[25],"to":[26,62,85,122],"insufficient":[27],"ground-truth":[28],"data":[29,110,129],"little":[31,151],"support":[32],"of":[33,36,160],"intra-class":[34,87],"variability":[35],"activities":[37,84],"(i.e.,":[38],"same":[40,55],"may":[42],"be":[43],"performed":[44],"different":[46,49,58],"ways":[47],"by":[48,53,77,99,134],"individuals,":[50],"or":[51],"even":[52],"individuals":[56],"with":[57,150],"time":[59],"frames).":[60],"Aiming":[61],"tackle":[63],"these":[64],"two":[65],"issues,":[66],"this":[68],"paper,":[69],"we":[70],"present":[71],"a":[72,95,158],"robust":[73],"approach":[76,91,156],"extracting":[78],"intrinsic":[80],"shared":[81],"structures":[82],"from":[83,104,138],"handle":[86],"variability,":[88],"is":[92],"embedded":[93],"into":[94],"semi-supervised":[96,171],"learning":[97,163],"framework":[98],"utilizing":[100],"learned":[102],"correlations":[103],"both":[105,117],"labeled":[106],"easily-obtained":[108],"unlabeled":[109],"simultaneously.":[111],"We":[112],"use":[113],"l2,1":[114],"minimization":[115],"on":[116,143],"loss":[118],"function":[119],"regularizations":[121],"effectively":[123],"resist":[124],"outliers":[125],"noisy":[127],"sensor":[128],"improve":[131],"accuracy":[133],"discerning":[135],"underlying":[136],"commonalities":[137],"activities.":[139],"Extensive":[140],"experimental":[141],"evaluations":[142],"four":[144],"community-contributed":[145],"public":[146],"datasets":[147],"indicate":[148],"that":[149],"training":[152],"samples,":[153],"our":[154],"proposed":[155,170],"outperforms":[157],"set":[159],"classical":[161],"supervised":[162],"methods":[164],"as":[165,167],"well":[166],"those":[168],"recently":[169],"approaches.":[172]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":10},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-09-16T00:00:00"}