{"id":"https://openalex.org/W3208059549","doi":"https://doi.org/10.1145/3459637.3482262","title":"HetMAML","display_name":"HetMAML","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3208059549","doi":"https://doi.org/10.1145/3459637.3482262","mag":"3208059549"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482262","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3459637.3482262","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3459637.3482262","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3459637.3482262","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100609080","display_name":"Jiayi Chen","orcid":"https://orcid.org/0000-0002-3541-8410"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiayi Chen","raw_affiliation_strings":["University of Virginia, Charlottesville, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013588572","display_name":"Aidong Zhang","orcid":"https://orcid.org/0000-0001-9723-3246"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aidong Zhang","raw_affiliation_strings":["University of Virginia, Charlottesville, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":1.0257,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.79992009,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"191","last_page":"200"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9972000122070312,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9958000183105469,"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/computer-science","display_name":"Computer science","score":0.8328324556350708},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6391071677207947},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5589056611061096},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5041161775588989},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.4824824631214142},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.47559794783592224},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4615730047225952},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.45734333992004395},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.42432671785354614},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.35206907987594604},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3354533314704895}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8328324556350708},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6391071677207947},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5589056611061096},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5041161775588989},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.4824824631214142},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.47559794783592224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4615730047225952},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.45734333992004395},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.42432671785354614},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.35206907987594604},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3354533314704895},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459637.3482262","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3459637.3482262","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3459637.3482262","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3459637.3482262","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3459637.3482262","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3459637.3482262","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6014851183","display_name":"III: Small: Multimodal Machine Learning for Data with Incomplete Modalities","funder_award_id":"2008208","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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3208059549.pdf","grobid_xml":"https://content.openalex.org/works/W3208059549.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1539811621","https://openalex.org/W1587447546","https://openalex.org/W1644641054","https://openalex.org/W1989085630","https://openalex.org/W2064675550","https://openalex.org/W2122563357","https://openalex.org/W2131774270","https://openalex.org/W2143926884","https://openalex.org/W2165092666","https://openalex.org/W2517194566","https://openalex.org/W2739799890","https://openalex.org/W2741295496","https://openalex.org/W2747172199","https://openalex.org/W2747329762","https://openalex.org/W2759083144","https://openalex.org/W2765291577","https://openalex.org/W2799162093","https://openalex.org/W2809410879","https://openalex.org/W2809469215","https://openalex.org/W2887761937","https://openalex.org/W2892880750","https://openalex.org/W2962805158","https://openalex.org/W2963573392","https://openalex.org/W2963919481","https://openalex.org/W2964010806","https://openalex.org/W2964105864","https://openalex.org/W2964121937","https://openalex.org/W2964249784","https://openalex.org/W2964346351","https://openalex.org/W2970105755","https://openalex.org/W3080565611","https://openalex.org/W3080670519","https://openalex.org/W4234552385","https://openalex.org/W4307050287"],"related_works":["https://openalex.org/W3200361725","https://openalex.org/W4319309271","https://openalex.org/W3092824172","https://openalex.org/W3105036711","https://openalex.org/W3199608561","https://openalex.org/W3020638616","https://openalex.org/W1504101963","https://openalex.org/W4213165337","https://openalex.org/W2940256401","https://openalex.org/W2954574047"],"abstract_inverted_index":{"Most":[0],"of":[1,33,47,80,95,139,142,149,169,186,215],"existing":[2],"gradient-based":[3],"meta-learning":[4,106],"approaches":[5],"to":[6,180],"few-shot":[7],"learning":[8],"assume":[9],"that":[10,29,38,76,135,195],"all":[11],"tasks":[12,34,41,71,143,206],"have":[13],"the":[14,21,30,45,57,112,121,137,145,167,176,181],"same":[15,146,182],"input":[16,31,48,138,171,178],"feature":[17,158],"space.":[18],"However,":[19],"in":[20,44,97],"real":[22],"world":[23],"scenarios,":[24],"there":[25,63],"are":[26],"many":[27],"cases":[28],"structures":[32,172],"can":[35,109,119,162],"be":[36],"different,":[37],"is,":[39],"different":[40],"may":[42],"vary":[43],"number":[46],"modalities":[49],"or":[50],"data":[51],"types.":[52],"Existing":[53],"meta-learners":[54],"cannot":[55],"handle":[56],"heterogeneous":[58,177,205],"task":[59,85],"distribution":[60],"(HTD)":[61],"as":[62],"is":[64],"not":[65],"only":[66],"global":[67],"meta-knowledge":[68],"shared":[69,116,202],"across":[70],"but":[72],"also":[73],"type-specific":[74,113,199],"knowledge":[75,117,124],"distinguishes":[77],"each":[78,93,140,213],"type":[79,94,141,214],"tasks.":[81,216],"To":[82],"deal":[83],"with":[84],"heterogeneity":[86],"and":[87,114,118,126,173,200,207],"promote":[88],"fast":[89,209],"within-task":[90,210],"adaptions":[91,211],"for":[92,204,212],"tasks,":[96],"this":[98],"paper,":[99],"we":[100,129,153],"propose":[101,154],"HetMAML,":[102],"a":[103,131,155],"task-heterogeneous":[104,192],"model-agnostic":[105],"framework,":[107],"which":[108,161],"capture":[110],"both":[111],"globally":[115,201],"achieve":[120],"balance":[122],"between":[123],"customization":[125],"generalization.":[127],"Specifically,":[128],"design":[130],"multi-channel":[132],"backbone":[133],"module":[134],"encodes":[136],"into":[144,165],"length":[147],"sequence":[148],"modality-specific":[150],"embeddings.":[151],"Then,":[152],"task-aware":[156],"iterative":[157],"aggregation":[159],"network":[160],"automatically":[163],"take":[164],"account":[166],"context":[168],"task-specific":[170],"adaptively":[174],"project":[175],"spaces":[179],"lower-dimensional":[183],"embedding":[184],"space":[185],"concepts.":[187],"Our":[188],"experiments":[189],"on":[190],"six":[191],"datasets":[193],"demonstrate":[194],"HetMAML":[196],"successfully":[197],"leverages":[198],"meta-parameters":[203],"achieves":[208]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2021-11-08T00:00:00"}