{"id":"https://openalex.org/W2907077903","doi":"https://doi.org/10.1109/wacv.2019.00142","title":"Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision","display_name":"Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2907077903","doi":"https://doi.org/10.1109/wacv.2019.00142","mag":"2907077903"},"language":"en","primary_location":{"id":"doi:10.1109/wacv.2019.00142","doi":"https://doi.org/10.1109/wacv.2019.00142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2019.00142","pdf_url":null,"source":{"id":"https://openalex.org/S4393918690","display_name":"IEEE Winter Conference on Applications of Computer Vision","issn_l":"2472-6737","issn":["2472-6737"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1901.01151","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046056596","display_name":"Vishal Kaushal","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vishal Kaushal","raw_affiliation_strings":["IIT Bombay, Mumbai, India","Indian Institute of Technology Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Indian Institute of Technology Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000529247","display_name":"Rishabh Iyer","orcid":"https://orcid.org/0000-0001-9851-463X","observed_orcids":["https://orcid.org/0000-0001-9851-463X"]},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rishabh Iyer","raw_affiliation_strings":["Microsoft Redmond, Washington, USA","(Microsoft)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Redmond, Washington, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"(Microsoft)","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035865886","display_name":"Suraj Nandkishor Kothawade","orcid":"https://orcid.org/0000-0001-9405-6862","observed_orcids":["https://orcid.org/0000-0001-9405-6862"]},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Suraj Kothawade","raw_affiliation_strings":["IIT Bombay, Mumbai, India","Indian Institute of Technology Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Indian Institute of Technology Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021708131","display_name":"Rohan Mahadev","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rohan Mahadev","raw_affiliation_strings":["AITOE Labs, Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AITOE Labs, Mumbai, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061856423","display_name":"Khoshrav Doctor","orcid":"https://orcid.org/0000-0003-4170-9430","observed_orcids":["https://orcid.org/0000-0003-4170-9430"]},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Khoshrav Doctor","raw_affiliation_strings":["University of Massachusetts, Massachusetts, USA","University of Massachusetts, Amherst"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts, Massachusetts, USA","institution_ids":[]},{"raw_affiliation_string":"University of Massachusetts, Amherst","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089606464","display_name":"Ganesh Ramakrishnan","orcid":"https://orcid.org/0000-0003-4533-2490","observed_orcids":["https://orcid.org/0000-0003-4533-2490"]},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ganesh Ramakrishnan","raw_affiliation_strings":["IIT Bombay, Mumbai, Maharashtra, India","Indian Institute of Technology Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Bombay, Mumbai, Maharashtra, India","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Indian Institute of Technology Bombay","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1208,"has_fulltext":true,"cited_by_count":51,"citation_normalized_percentile":{"value":0.90887554,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1289","last_page":"1299"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9688000082969666,"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":0.9688000082969666,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.014600000344216824,"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":0.011500000022351742,"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/active-learning-machine-learning","display_name":"active learning (machine learning)","score":0.9959999918937683},{"id":"https://openalex.org/keywords/facility-location-model","display_name":"facility location model","score":0.8410000205039978},{"id":"https://openalex.org/keywords/dispersion-model","display_name":"dispersion model","score":0.9900000095367432},{"id":"https://openalex.org/keywords/uncertainty-sampling","display_name":"uncertainty sampling","score":0.8510000109672546},{"id":"https://openalex.org/keywords/limited-training-data","display_name":"limited training data","score":0.7020000219345093},{"id":"https://openalex.org/keywords/gender-classification","display_name":"gender classification","score":0.8460000157356262},{"id":"https://openalex.org/keywords/face-recognition","display_name":"face recognition","score":0.9980000257492065},{"id":"https://openalex.org/keywords/scene-classification","display_name":"scene classification","score":0.9929999709129333},{"id":"https://openalex.org/keywords/object-detection","display_name":"object detection","score":0.9919999837875366},{"id":"https://openalex.org/keywords/object-recognition","display_name":"object recognition","score":0.878000020980835},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9359999895095825}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.769778847694397},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7631884813308716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6704525947570801},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5768385529518127},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5722109079360962},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47771620750427246},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.4671610891819},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4273248314857483},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.41542333364486694},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33322325348854065},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/wacv.2019.00142","doi":"https://doi.org/10.1109/wacv.2019.00142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2019.00142","pdf_url":null,"source":{"id":"https://openalex.org/S4393918690","display_name":"IEEE Winter Conference on Applications of Computer Vision","issn_l":"2472-6737","issn":["2472-6737"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1901.01151","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1901.01151","pdf_url":"https://arxiv.org/pdf/1901.01151","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2907077903","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1901.01151","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:dsapce.library.iitb.ac.in:100/27978","doi":null,"is_oa":false,"landing_page_url":"http://dspace.library.iitb.ac.in/xmlui/handle/100/27978","pdf_url":null,"source":{"id":"https://openalex.org/S4306400899","display_name":"DSpace (IIT Bombay)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I162827531","host_organization_name":"Indian Institute of Technology Bombay","host_organization_lineage":["https://openalex.org/I162827531"],"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 Paper"},{"id":"doi:10.48550/arxiv.1901.01151","doi":"https://doi.org/10.48550/arxiv.1901.01151","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1901.01151","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1901.01151","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1901.01151","pdf_url":"https://arxiv.org/pdf/1901.01151","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2907077903.pdf","grobid_xml":"https://content.openalex.org/works/W2907077903.grobid-xml"},"referenced_works_count":71,"referenced_works":["https://openalex.org/W52746146","https://openalex.org/W639708223","https://openalex.org/W1026270304","https://openalex.org/W1482849335","https://openalex.org/W1483870316","https://openalex.org/W1506491340","https://openalex.org/W1536680647","https://openalex.org/W1680189815","https://openalex.org/W1686810756","https://openalex.org/W1821462560","https://openalex.org/W1849277567","https://openalex.org/W1898824936","https://openalex.org/W1904325426","https://openalex.org/W1905153633","https://openalex.org/W1912128066","https://openalex.org/W1965804146","https://openalex.org/W1984985727","https://openalex.org/W1994488211","https://openalex.org/W2003381716","https://openalex.org/W2023672749","https://openalex.org/W2080021732","https://openalex.org/W2085989833","https://openalex.org/W2096733369","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2124033848","https://openalex.org/W2125653933","https://openalex.org/W2128678390","https://openalex.org/W2132560759","https://openalex.org/W2134670479","https://openalex.org/W2134797427","https://openalex.org/W2138779671","https://openalex.org/W2140609507","https://openalex.org/W2144933361","https://openalex.org/W2145287260","https://openalex.org/W2149933564","https://openalex.org/W2152161678","https://openalex.org/W2155541015","https://openalex.org/W2155893237","https://openalex.org/W2156749117","https://openalex.org/W2159291411","https://openalex.org/W2163605009","https://openalex.org/W2165698076","https://openalex.org/W2166049352","https://openalex.org/W2171671120","https://openalex.org/W2187105870","https://openalex.org/W2194775991","https://openalex.org/W2247953682","https://openalex.org/W2251306702","https://openalex.org/W2273048275","https://openalex.org/W2289084343","https://openalex.org/W2325939864","https://openalex.org/W2432717477","https://openalex.org/W2570343428","https://openalex.org/W2576271642","https://openalex.org/W2606195968","https://openalex.org/W2750912449","https://openalex.org/W2803409734","https://openalex.org/W2903158431","https://openalex.org/W2949667497","https://openalex.org/W2950276680","https://openalex.org/W2951433694","https://openalex.org/W2951548327","https://openalex.org/W2951911250","https://openalex.org/W2963341924","https://openalex.org/W4394670654","https://openalex.org/W6680902425","https://openalex.org/W6695314431","https://openalex.org/W7098642242"],"related_works":["https://openalex.org/W2806138827","https://openalex.org/W4390535086","https://openalex.org/W2747928781","https://openalex.org/W3158091537","https://openalex.org/W7125574254","https://openalex.org/W3113682753","https://openalex.org/W2801356621","https://openalex.org/W1912128066","https://openalex.org/W3040475362","https://openalex.org/W2118236796"],"abstract_inverted_index":{"Supervised":[0],"machine":[1,203],"learning":[2,38,89,204],"based":[3,109,167],"state-of-the-art":[4],"computer":[5,147],"vision":[6,148],"techniques":[7,39],"are":[8],"in":[9,90,171,188,190],"general":[10],"data":[11,14,33,77,194,214],"hungry.":[12],"Their":[13],"curation":[15],"poses":[16],"the":[17,85,101,105,117,124,141,172,177,199],"challenges":[18],"of":[19,52,59,87,100,119,146,201],"expensive":[20],"human":[21,93],"labeling,":[22],"inadequate":[23],"computing":[24],"resources":[25],"and":[26,36,62,64,126,133,159,215],"larger":[27],"experiment":[28],"turn":[29],"around":[30],"times.":[31],"Training":[32],"subset":[34,53,78,99,131,168],"selection":[35,54,132,169],"active":[37,88],"have":[40],"been":[41],"proposed":[42],"as":[43],"possible":[44],"solutions":[45],"to":[46,68],"these":[47],"challenges.":[48],"A":[49],"special":[50],"class":[51],"functions":[55],"naturally":[56],"model":[57],"notions":[58],"diversity,":[60],"coverage":[61],"representation":[63],"can":[65,81,175],"be":[66],"used":[67],"eliminate":[69],"redundancy":[70],"thus":[71],"lending":[72],"themselves":[73],"well":[74],"for":[75,129,143],"training":[76,193,200,213],"selection.":[79],"They":[80],"also":[82],"help":[83],"improve":[84],"efficiency":[86],"further":[91],"reducing":[92,134],"labeling":[94,135,216],"efforts":[95],"by":[96,179],"selecting":[97],"a":[98,144],"examples":[102],"obtained":[103],"using":[104],"conventional":[106],"uncertainty":[107],"sampling":[108],"techniques.":[110],"In":[111],"this":[112,139],"work,":[113],"we":[114],"empirically":[115],"demonstrate":[116,138],"effectiveness":[118],"two":[120],"diversity":[121,166],"models,":[122],"namely":[123],"Facility-Location":[125],"Dispersion":[127],"models":[128,205],"training-data":[130],"effort.":[136],"We":[137],"across":[140],"board":[142],"variety":[145],"tasks":[149],"including":[150],"Gender":[151],"Recognition,":[152,154,156],"Face":[153],"Scene":[155],"Object":[157,160],"Detection":[158],"Recognition.":[161],"Our":[162],"results":[163],"show":[164],"that":[165],"done":[170],"right":[173],"way":[174],"increase":[176],"accuracy":[178],"upto":[180],"5":[181],"-":[182],"10%":[183],"over":[184],"existing":[185],"baselines,":[186],"particularly":[187],"settings":[189],"which":[191],"less":[192,212],"is":[195],"available.":[196],"This":[197],"allows":[198],"complex":[202],"like":[206],"Convolutional":[207],"Neural":[208],"Networks":[209],"with":[210],"much":[211],"costs":[217],"while":[218],"incurring":[219],"minimal":[220],"performance":[221],"loss.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2019-01-11T00:00:00"}
