{"id":"https://openalex.org/W3001178834","doi":"https://doi.org/10.1145/3336191.3371874","title":"Learning with Small Data","display_name":"Learning with Small Data","publication_year":2020,"publication_date":"2020-01-20","ids":{"openalex":"https://openalex.org/W3001178834","doi":"https://doi.org/10.1145/3336191.3371874","mag":"3001178834"},"language":"en","primary_location":{"id":"doi:10.1145/3336191.3371874","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3336191.3371874","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3336191.3371874","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3336191.3371874","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016516907","display_name":"Zhenhui Li","orcid":"https://orcid.org/0000-0001-7221-2588"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhenhui Li","raw_affiliation_strings":["Pennsylvania State University, State College, PA, USA"],"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051534896","display_name":"Huaxiu Yao","orcid":"https://orcid.org/0000-0002-8691-9629"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huaxiu Yao","raw_affiliation_strings":["Pennsylvania State University, State College, PA, USA"],"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001030192","display_name":"Fenglong Ma","orcid":"https://orcid.org/0000-0002-4999-0303"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fenglong Ma","raw_affiliation_strings":["Pennsylvania State University, State College, PA, USA"],"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5016516907"],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":1.4953,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.86007926,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"884","last_page":"887"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9998999834060669,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","score":0.9955000281333923,"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":0.9947999715805054,"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/computer-science","display_name":"Computer science","score":0.7973489761352539},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.6899912357330322},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6718367338180542},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5257652401924133},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.48226839303970337},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48151740431785583},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.47299131751060486},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.45239511132240295},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.41514936089515686},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4040616452693939},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.18458572030067444}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7973489761352539},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.6899912357330322},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6718367338180542},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5257652401924133},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.48226839303970337},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48151740431785583},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.47299131751060486},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.45239511132240295},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.41514936089515686},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4040616452693939},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.18458572030067444},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3336191.3371874","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3336191.3371874","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3336191.3371874","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3336191.3371874","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3336191.3371874","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3336191.3371874","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G1977798577","display_name":null,"funder_award_id":"1652525,1618448","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4342645261","display_name":null,"funder_award_id":"1618448","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3001178834.pdf","grobid_xml":"https://content.openalex.org/works/W3001178834.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1565327149","https://openalex.org/W1630959083","https://openalex.org/W2048679005","https://openalex.org/W2099471712","https://openalex.org/W2148143831","https://openalex.org/W2250635077","https://openalex.org/W2434014514","https://openalex.org/W2525579820","https://openalex.org/W2557074642","https://openalex.org/W2561529111","https://openalex.org/W2593768305","https://openalex.org/W2601450892","https://openalex.org/W2766363782","https://openalex.org/W2767286446","https://openalex.org/W2788364218","https://openalex.org/W2788798739","https://openalex.org/W2805481182","https://openalex.org/W2809398771","https://openalex.org/W2888541716","https://openalex.org/W2896538705","https://openalex.org/W2903158431","https://openalex.org/W2903721568","https://openalex.org/W2904167876","https://openalex.org/W2911752602","https://openalex.org/W2914241418","https://openalex.org/W2946757877","https://openalex.org/W2950763986","https://openalex.org/W2951670162","https://openalex.org/W2951775809","https://openalex.org/W2951970475","https://openalex.org/W2953070460","https://openalex.org/W2962723986","https://openalex.org/W2963341924","https://openalex.org/W2963444553","https://openalex.org/W2963593215","https://openalex.org/W2963687836","https://openalex.org/W2964078140","https://openalex.org/W2964207259","https://openalex.org/W2964268978","https://openalex.org/W2964278684","https://openalex.org/W2971973261","https://openalex.org/W2982455176","https://openalex.org/W2997198750","https://openalex.org/W2997738974"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W2482350142","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4288019534","https://openalex.org/W4210468674"],"abstract_inverted_index":{"In":[0,76],"the":[1,24,66,81,95,106,120],"era":[2],"of":[3,15,90,97,109],"big":[4],"data,":[5],"it":[6],"is":[7,43,135],"easy":[8],"for":[9],"us":[10],"collect":[11],"a":[12,87],"huge":[13],"number":[14],"image":[16],"and":[17,38,117,138,151,155],"text":[18],"data.":[19],"However,":[20],"we":[21,63,78],"frequently":[22],"face":[23],"real-world":[25],"problems":[26],"with":[27,53],"only":[28],"small":[29,54,73],"(labeled)":[30],"data":[31,74,124,144],"in":[32,60,93,142],"some":[33],"domains,":[34],"such":[35,127],"as":[36,128],"healthcare":[37],"urban":[39],"computing.":[40],"The":[41],"challenge":[42],"how":[44],"to":[45,71,123],"make":[46],"machine":[47,68,114],"learn":[48],"algorithms":[49],"still":[50],"work":[51],"well":[52],"data?":[55],"To":[56],"solve":[57],"this":[58,61,134],"challenge,":[59],"tutorial,":[62],"will":[64,147],"cover":[65],"state-of-the-art":[67],"learning":[69,115],"techniques":[70,108],"handle":[72],"issue.":[75],"particular,":[77],"focus":[79],"on":[80,102],"following":[82],"three":[83],"aspects:":[84],"(1)":[85],"Providing":[86],"comprehensive":[88],"review":[89],"recent":[91],"advances":[92],"exploring":[94],"power":[96],"knowledge":[98,112],"transfer,":[99],"especially":[100],"focusing":[101],"meta-learning;":[103],"(2)":[104],"introducing":[105],"cutting-edge":[107],"incorporating":[110],"human/expert":[111],"into":[113],"models;":[116],"(3)":[118],"identifying":[119],"open":[121],"challenges":[122],"augmentation":[125],"techniques,":[126],"generative":[129],"adversarial":[130],"networks.":[131],"We":[132],"believe":[133],"an":[136],"emerging":[137],"potentially":[139],"high-impact":[140],"topic":[141],"computational":[143],"science,":[145],"which":[146],"attract":[148],"both":[149],"researchers":[150],"practitioners":[152],"from":[153],"academia":[154],"industry.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}