{"id":"https://openalex.org/W2925201588","doi":null,"title":"Max-margin zero-shot learning for multi-class classification","display_name":"Max-margin zero-shot learning for multi-class classification","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2925201588","mag":"2925201588"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.673.6457","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.673.6457","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cis.temple.edu/%7Eyuhong/research/papers/aistats15b.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xin Li","orcid":"https://orcid.org/0000-0002-9244-6485","observed_orcids":["https://orcid.org/0000-0002-9244-6485"]},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-9244-6485","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5043824291","display_name":"Yuhong Guo","orcid":"https://orcid.org/0000-0002-7621-342X","observed_orcids":["https://orcid.org/0000-0002-7621-342X"]},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuhong Guo","raw_affiliation_strings":["Temple University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Temple University","institution_ids":["https://openalex.org/I84392919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.1262,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.94277562,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":"38","issue":null,"first_page":"626","last_page":"634"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994999766349792,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994999766349792,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0003000000142492354,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/zero-shot-learning","display_name":"zero-shot learning","score":0.9940000176429749},{"id":"https://openalex.org/keywords/max-margin-learning","display_name":"max-margin learning","score":0.9100000262260437},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"multi-class classification","score":0.9070000052452087},{"id":"https://openalex.org/keywords/semi-supervised-classification","display_name":"semi-supervised classification","score":0.9340000152587891},{"id":"https://openalex.org/keywords/unsupervised-clustering","display_name":"unsupervised clustering","score":0.9269999861717224},{"id":"https://openalex.org/keywords/label-embedding","display_name":"label embedding","score":0.9330000281333923},{"id":"https://openalex.org/keywords/semantic-knowledge","display_name":"semantic knowledge","score":0.574999988079071},{"id":"https://openalex.org/keywords/dual-formulation","display_name":"dual formulation","score":0.5770000219345093},{"id":"https://openalex.org/keywords/image-classification","display_name":"image classification","score":0.6710000038146973}],"concepts":[{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7889206409454346},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7281610369682312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6173486113548279},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5936400890350342},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5751404166221619},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.5664145946502686},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5437293648719788},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.5429522395133972},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4880200922489166},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4761647880077362},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40075188875198364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37120765447616577},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.673.6457","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.673.6457","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cis.temple.edu/%7Eyuhong/research/papers/aistats15b.pdf","raw_type":"text"},{"id":"mag:2925201588","doi":null,"is_oa":false,"landing_page_url":"https://ir.library.carleton.ca/pub/19712","pdf_url":null,"source":{"id":"https://openalex.org/S118988714","display_name":"Journal of Machine Learning Research","issn_l":"1532-4435","issn":["1532-4435","1533-7928"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-a","cwts-core","dongbi-a","jufo-3","ki-jl-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Journal of Machine Learning Research","raw_type":null},{"id":"mag:331145617","doi":null,"is_oa":false,"landing_page_url":"http://proceedings.mlr.press/v38/li15d.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419146","display_name":"International Conference on Artificial Intelligence and Statistics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Artificial Intelligence and Statistics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2202374479","https://openalex.org/W2792455007","https://openalex.org/W2494196141","https://openalex.org/W2887575628","https://openalex.org/W3128601789","https://openalex.org/W2951560603","https://openalex.org/W7100495863","https://openalex.org/W3025645599","https://openalex.org/W3137518533","https://openalex.org/W3088517856"],"abstract_inverted_index":{"Due":[0],"to":[1,22,65,92,106,113],"the":[2,9,34,49,57,108,120,123],"dramatic":[3],"expanse":[4],"of":[5,11,31,87,122],"data":[6,104],"cat-egories":[7],"and":[8,56],"lack":[10],"labeled":[12],"instances,":[13],"zero-shot":[14,67,94],"learning,":[15],"which":[16],"transfers":[17],"knowledge":[18,91],"from":[19,33],"observed":[20],"classes":[21,55,63],"recognize":[23],"unseen":[24,62],"classes,":[25],"has":[26],"started":[27],"drawing":[28],"a":[29,42,80],"lot":[30],"attention":[32],"research":[35],"community.":[36],"In":[37],"this":[38,76],"paper,":[39],"we":[40,78],"propose":[41],"semi-supervised":[43,50],"max-margin":[44],"learning":[45],"framework":[46],"that":[47,83],"integrates":[48],"classification":[51],"problem":[52,60],"over":[53,61],"ob-served":[54],"unsupervised":[58],"cluster-ing":[59],"together":[64],"tackle":[66],"multi-class":[68],"classification.":[69],"By":[70],"further":[71],"integrating":[72],"label":[73,89],"embedding":[74],"into":[75],"framework,":[77],"produce":[79],"dual":[81],"formulation":[82],"permits":[84],"convenient":[85],"incorporation":[86],"aux-iliary":[88],"semantic":[90],"improve":[93],"learning.":[95],"We":[96],"conduct":[97],"extensive":[98],"ex-periments":[99],"on":[100],"three":[101],"standard":[102],"image":[103],"sets":[105],"evaluate":[107],"proposed":[109],"approach":[110],"by":[111],"com-paring":[112],"two":[114],"state-of-the-art":[115],"methods.":[116],"Our":[117],"results":[118],"demonstrate":[119],"efficacy":[121],"pro-posed":[124],"framework.":[125],"1":[126]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2019-04-01T00:00:00"}