{"id":"https://openalex.org/W4403780876","doi":"https://doi.org/10.1145/3664647.3681446","title":"FSL-QuickBoost: Minimal-Cost Ensemble for Few-Shot Learning","display_name":"FSL-QuickBoost: Minimal-Cost Ensemble for Few-Shot Learning","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403780876","doi":"https://doi.org/10.1145/3664647.3681446"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3681446","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3664647.3681446","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3664647.3681446?download=true","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","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/10.1145/3664647.3681446?download=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107933482","display_name":"Y. Bai","orcid":"https://orcid.org/0009-0009-9200-5469"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Yunwei Bai","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074760532","display_name":"Bill Cai","orcid":"https://orcid.org/0000-0002-1381-5247"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bill Yang Cai","raw_affiliation_strings":["Amazon Web Services, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Amazon Web Services, Singapore, Singapore","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044788592","display_name":"Ying Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ying Kiat Tan","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027804169","display_name":"Zangwei Zheng","orcid":"https://orcid.org/0000-0002-1505-1535"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zangwei Zheng","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071943020","display_name":"Shiming Chen","orcid":"https://orcid.org/0000-0001-9633-3392"},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Shiming Chen","raw_affiliation_strings":["Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates"],"affiliations":[{"raw_affiliation_string":"Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210113480"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000454484","display_name":"Tsuhan Chen","orcid":"https://orcid.org/0000-0003-3951-7931"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Tsuhan Chen","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5107933482"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16460748,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8326","last_page":"8335"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9843000173568726,"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":0.6947740912437439},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5739041566848755},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4797181487083435},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.45578211545944214},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.41025203466415405},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34834545850753784},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.0958055853843689},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08703866600990295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6947740912437439},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5739041566848755},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4797181487083435},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.45578211545944214},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.41025203466415405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34834545850753784},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0958055853843689},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08703866600990295},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3664647.3681446","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3664647.3681446","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3664647.3681446?download=true","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:dspace.mit.edu:1721.1/157613","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/157613","pdf_url":"https://dspace.mit.edu/bitstream/1721.1/157613/1/3664647.3681446.pdf","source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Association for Computing Machinery","raw_type":"http://purl.org/eprint/type/ConferencePaper"}],"best_oa_location":{"id":"doi:10.1145/3664647.3681446","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3664647.3681446","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3664647.3681446?download=true","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1795493338","display_name":null,"funder_award_id":"MOE-MOET32022-0001","funder_id":"https://openalex.org/F4320320751","funder_display_name":"Ministry of Education - Singapore"}],"funders":[{"id":"https://openalex.org/F4320320751","display_name":"Ministry of Education - Singapore","ror":"https://ror.org/01kcva023"},{"id":"https://openalex.org/F4320322724","display_name":"Ministry of Education, India","ror":"https://ror.org/048xjjh50"},{"id":"https://openalex.org/F4320323346","display_name":"B\u1ed9 Gi\u00e1o d\u1ee5c v\u00e0 \u00d0\u00e0o t\u1ea1o","ror":"https://ror.org/00drv3378"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403780876.pdf","grobid_xml":"https://content.openalex.org/works/W4403780876.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W605727707","https://openalex.org/W1999478155","https://openalex.org/W2117539524","https://openalex.org/W2145073242","https://openalex.org/W2194775991","https://openalex.org/W2540093921","https://openalex.org/W2612690371","https://openalex.org/W2616247523","https://openalex.org/W2625674597","https://openalex.org/W2798836702","https://openalex.org/W2804074543","https://openalex.org/W2963070905","https://openalex.org/W2963078860","https://openalex.org/W2963538198","https://openalex.org/W2963545832","https://openalex.org/W2963845150","https://openalex.org/W2963943197","https://openalex.org/W2964105864","https://openalex.org/W2982049331","https://openalex.org/W2988205463","https://openalex.org/W3012255272","https://openalex.org/W3034312118","https://openalex.org/W3046220160","https://openalex.org/W3092600962","https://openalex.org/W3097217077","https://openalex.org/W3102564565","https://openalex.org/W3174159092","https://openalex.org/W3203055845","https://openalex.org/W3209654711","https://openalex.org/W4213457947","https://openalex.org/W4281956361","https://openalex.org/W4295276204","https://openalex.org/W4296642586","https://openalex.org/W4300973708","https://openalex.org/W4313167301","https://openalex.org/W4389138872","https://openalex.org/W4402702970","https://openalex.org/W6681651645"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W2497720472","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4292659306","https://openalex.org/W4364306694"],"abstract_inverted_index":{"Few-shot":[0],"learning":[1],"(FSL)":[2],"usually":[3,51],"trains":[4],"models":[5,112],"on":[6,16,101,117],"data":[7,17],"from":[8,18],"one":[9],"set":[10,21],"of":[11,22,30,45,84],"classes,":[12,23],"but":[13],"tests":[14],"them":[15],"a":[19,25,35,94],"different":[20],"providing":[24],"few":[26],"labeled":[27],"support":[28],"samples":[29],"the":[31,38,43,58,82,109],"unseen":[32],"classes":[33],"as":[34],"reference":[36],"for":[37,80],"trained":[39],"model.":[40],"Due":[41],"to":[42,57],"lack":[44],"target-relevant":[46],"training":[47],"data,":[48],"there":[49],"is":[50,76,106],"high":[52],"generalization":[53,83],"error":[54],"with":[55,93,108,127],"respect":[56],"test":[59],"classes.":[60],"In":[61],"this":[62],"work,":[63],"we":[64],"conduct":[65],"empirical":[66],"explorations":[67],"and":[68,78,105],"propose":[69],"an":[70,89],"ensemble":[71],"method":[72,123],"(namely":[73,98],"QuickBoost),":[74],"which":[75],"efficient":[77],"effective":[79],"improving":[81],"FSL.":[85],"Specifically,":[86],"QuickBoost":[87],"includes":[88],"alternative-architecture":[90],"pretrained":[91],"encoder":[92],"one-vs-all":[95],"binary":[96],"classifier":[97],"FSL-Forest)":[99],"based":[100],"random":[102],"forest":[103],"algorithm,":[104],"ensembled":[107],"off-the-shelf":[110],"FSL":[111],"via":[113],"logit-level":[114],"averaging.":[115],"Experiments":[116],"three":[118],"benchmarks":[119],"demonstrate":[120],"that":[121],"our":[122],"achieves":[124],"state-of-the-art":[125],"performance":[126],"good":[128],"efficiency.":[129],"Codes":[130],"are":[131],"available":[132],"at":[133],"https://github.com/WendyBaiYunwei/FSL-QuickBoost.":[134]},"counts_by_year":[],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}