{"id":"https://openalex.org/W2978237714","doi":"https://doi.org/10.1109/ijcnn.2019.8851824","title":"Recurrent Network and Multi-arm Bandit Methods for Multi-task Learning without Task Specification","display_name":"Recurrent Network and Multi-arm Bandit Methods for Multi-task Learning without Task Specification","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978237714","doi":"https://doi.org/10.1109/ijcnn.2019.8851824","mag":"2978237714"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8851824","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851824","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038035260","display_name":"Thy Nguyen","orcid":null},"institutions":[{"id":"https://openalex.org/I119942284","display_name":"Missouri State University","ror":"https://ror.org/01d2sez20","country_code":"US","type":"education","lineage":["https://openalex.org/I119942284"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Thy Nguyen","raw_affiliation_strings":["Computer Science Dept., Missouri State University, Springfield, MO"],"affiliations":[{"raw_affiliation_string":"Computer Science Dept., Missouri State University, Springfield, MO","institution_ids":["https://openalex.org/I119942284"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040578359","display_name":"Tayo Obafemi-Ajayi","orcid":"https://orcid.org/0000-0002-0155-9733"},"institutions":[{"id":"https://openalex.org/I119942284","display_name":"Missouri State University","ror":"https://ror.org/01d2sez20","country_code":"US","type":"education","lineage":["https://openalex.org/I119942284"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tayo Obafemi-Ajayi","raw_affiliation_strings":["Computer Science Dept., Missouri State University, Springfield, MO"],"affiliations":[{"raw_affiliation_string":"Computer Science Dept., Missouri State University, Springfield, MO","institution_ids":["https://openalex.org/I119942284"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5038035260"],"corresponding_institution_ids":["https://openalex.org/I119942284"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11856331,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"8"},"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":0.9994000196456909,"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":0.9994000196456909,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7135021686553955},{"id":"https://openalex.org/keywords/reset","display_name":"Reset (finance)","score":0.6349892616271973},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6348581910133362},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6341758966445923},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6306993961334229},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5791756510734558},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5446751117706299},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5399662256240845},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5396023392677307},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.47522714734077454},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.433625191450119},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42822664976119995},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.42072880268096924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7135021686553955},{"id":"https://openalex.org/C2779795794","wikidata":"https://www.wikidata.org/wiki/Q7315343","display_name":"Reset (finance)","level":2,"score":0.6349892616271973},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6348581910133362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6341758966445923},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6306993961334229},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5791756510734558},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5446751117706299},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5399662256240845},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5396023392677307},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.47522714734077454},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.433625191450119},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42822664976119995},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.42072880268096924},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2019.8851824","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851824","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:bearworks.missouristate.edu:articles-cnas-2137","is_oa":false,"landing_page_url":"https://bearworks.missouristate.edu/articles-cnas/1138","pdf_url":null,"source":{"id":"https://openalex.org/S4377196450","display_name":"BearWorks (Missouri State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I119942284","host_organization_name":"Missouri State University","host_organization_lineage":["https://openalex.org/I119942284"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"College of Natural and Applied Sciences","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W581956982","https://openalex.org/W1526726828","https://openalex.org/W1544426622","https://openalex.org/W1689711448","https://openalex.org/W1942758450","https://openalex.org/W1944301273","https://openalex.org/W1986744686","https://openalex.org/W1998635907","https://openalex.org/W2064675550","https://openalex.org/W2065180801","https://openalex.org/W2076167926","https://openalex.org/W2108114251","https://openalex.org/W2116261113","https://openalex.org/W2118099552","https://openalex.org/W2153756422","https://openalex.org/W2165644552","https://openalex.org/W2182361439","https://openalex.org/W2186054958","https://openalex.org/W2187705271","https://openalex.org/W2472819217","https://openalex.org/W2523246573","https://openalex.org/W2558150900","https://openalex.org/W2577408049","https://openalex.org/W2590714056","https://openalex.org/W2593203636","https://openalex.org/W2604763608","https://openalex.org/W2742079690","https://openalex.org/W2913340405","https://openalex.org/W2949201716","https://openalex.org/W2950929549","https://openalex.org/W2963341924","https://openalex.org/W2963371846","https://openalex.org/W2963775850","https://openalex.org/W4300001399","https://openalex.org/W6616837769","https://openalex.org/W6632462264","https://openalex.org/W6640648879","https://openalex.org/W6640786210","https://openalex.org/W6676576766","https://openalex.org/W6677419484","https://openalex.org/W6684671274","https://openalex.org/W6685961532","https://openalex.org/W6686819018","https://openalex.org/W6717367658","https://openalex.org/W6717697761","https://openalex.org/W6720057410","https://openalex.org/W6727249380","https://openalex.org/W6730493114","https://openalex.org/W6736057607","https://openalex.org/W6742058293","https://openalex.org/W6745921498"],"related_works":["https://openalex.org/W350273603","https://openalex.org/W2393495588","https://openalex.org/W96259911","https://openalex.org/W2168225754","https://openalex.org/W4385608460","https://openalex.org/W2370772865","https://openalex.org/W1528611913","https://openalex.org/W2000034628","https://openalex.org/W2387487224","https://openalex.org/W4366146733"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,12,23,42,56,64,75,88,93,96,116,139,160],"problem":[4,24],"of":[5,25,27,127,163],"multi-task":[6],"learning":[7,109],"(MTL)":[8],"in":[9,103,136],"settings":[10],"where":[11],"task":[13,31,76,106,129,133],"assignment":[14],"is":[15,45,71,84,141],"not":[16],"known.":[17],"We":[18,98],"propose":[19],"two":[20,100],"mechanisms":[21],"for":[22,92],"inference":[26],"task's":[28],"parameter":[29,33,36,40,44,65,69,90,122,140],"without":[30,105,130],"specification:":[32],"adaptation":[34],"and":[35,110,174],"selection":[37,66,176],"methods.":[38],"In":[39,113],"adaptation,":[41],"model's":[43],"iteratively":[46],"updated":[47],"using":[48],"a":[49,68,81,125],"recurrent":[50],"neural":[51],"network":[52],"(RNN)":[53],"learner":[54],"as":[55],"mechanism":[57],"to":[58,60,86,119,124,143,147,150,168],"adapt":[59],"different":[61,101,128,151],"tasks.":[62,152],"For":[63],"model,":[67],"matrix":[70],"learned":[72],"beforehand":[73],"with":[74,166],"known":[77],"apriori.":[78],"During":[79],"testing,":[80],"bandit":[82,175],"algorithm":[83],"utilized":[85],"determine":[87],"appropriate":[89],"vector":[91],"model":[94,117],"on":[95,154],"fly.":[97],"explored":[99],"scenarios":[102],"MTL":[104,172],"specification,":[107],"continuous":[108,114],"reset":[111,137,142],"learning.":[112],"learning,":[115,138],"has":[118],"adjust":[120],"its":[121],"continuously":[123],"number":[126],"knowing":[131],"when":[132],"changes.":[134],"Whereas":[135],"an":[144],"initial":[145],"value":[146],"aid":[148],"transition":[149],"Results":[153],"three":[155],"real":[156],"benchmark":[157],"datasets":[158],"demonstrate":[159],"comparative":[161],"performance":[162],"both":[164],"models":[165],"respect":[167],"multiple":[169],"RNN":[170],"configurations,":[171],"algorithms":[173],"policies.":[177]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}