{"id":"https://openalex.org/W2962898908","doi":"https://doi.org/10.1145/3233547.3233554","title":"Robust Actor-Critic Contextual Bandit for Mobile Health (mHealth) Interventions","display_name":"Robust Actor-Critic Contextual Bandit for Mobile Health (mHealth) Interventions","publication_year":2018,"publication_date":"2018-08-15","ids":{"openalex":"https://openalex.org/W2962898908","doi":"https://doi.org/10.1145/3233547.3233554","mag":"2962898908"},"language":"en","primary_location":{"id":"doi:10.1145/3233547.3233554","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3233547.3233554","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3233547.3233554","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","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/10.1145/3233547.3233554","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103796253","display_name":"Feiyun Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feiyun Zhu","raw_affiliation_strings":["The University of Texas at Arlington, Arlington, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas at Arlington, Arlington, TX, USA","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080121038","display_name":"Jun Guo","orcid":"https://orcid.org/0000-0001-7525-3617"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Guo","raw_affiliation_strings":["University of Michigan, Ann Arbor, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, TX, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100713352","display_name":"Ruoyu Li","orcid":"https://orcid.org/0009-0006-9741-6644"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruoyu Li","raw_affiliation_strings":["The University of Texas at Arlington, Arlington, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas at Arlington, Arlington, TX, USA","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068865316","display_name":"Junzhou Huang","orcid":"https://orcid.org/0000-0002-9548-1227"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junzhou Huang","raw_affiliation_strings":["The University of Texas at Arlington; Tencent AI Lab, Arlington, TX, USA","The University of Texas at Arlington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas at Arlington; Tencent AI Lab, Arlington, TX, USA","institution_ids":["https://openalex.org/I189196454"]},{"raw_affiliation_string":"The University of Texas at Arlington","institution_ids":["https://openalex.org/I189196454"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"492","last_page":"501"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":1.0,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9872000217437744,"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/outlier","display_name":"Outlier","score":0.8337969779968262},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6525130271911621},{"id":"https://openalex.org/keywords/mhealth","display_name":"mHealth","score":0.5639296174049377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5094669461250305},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.48013874888420105},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4556366503238678},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.444816529750824},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4143342971801758},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35686880350112915},{"id":"https://openalex.org/keywords/psychological-intervention","display_name":"Psychological intervention","score":0.21596035361289978}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8337969779968262},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6525130271911621},{"id":"https://openalex.org/C2779363104","wikidata":"https://www.wikidata.org/wiki/Q17069079","display_name":"mHealth","level":3,"score":0.5639296174049377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5094669461250305},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.48013874888420105},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4556366503238678},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.444816529750824},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4143342971801758},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35686880350112915},{"id":"https://openalex.org/C27415008","wikidata":"https://www.wikidata.org/wiki/Q7256382","display_name":"Psychological intervention","level":2,"score":0.21596035361289978},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3233547.3233554","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3233547.3233554","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3233547.3233554","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3233547.3233554","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3233547.3233554","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3233547.3233554","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.8399999737739563,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G1183982361","display_name":null,"funder_award_id":"CMMI-1434401","funder_id":"https://openalex.org/F4320337391","funder_display_name":"Division of Civil, Mechanical and Manufacturing Innovation"},{"id":"https://openalex.org/G3387330441","display_name":null,"funder_award_id":"CAREER","funder_id":"https://openalex.org/F4320337391","funder_display_name":"Division of Civil, Mechanical and Manufacturing Innovation"},{"id":"https://openalex.org/G3719915608","display_name":"III: Small: Collaborative Research: Robust Materials Genome Data Mining Framework for Prediction and Guidance of Nanoparticle Synthesis","funder_award_id":"1423056","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3876414547","display_name":null,"funder_award_id":"IIS-1553687","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3998233361","display_name":null,"funder_award_id":"IIS-1718853","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G462345853","display_name":null,"funder_award_id":"IIS-1423056, CMMI-1434401, CNS-1405985","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6105257721","display_name":"Statistics-based Optimization Methods for Adaptive Interdisciplinary Pain Management","funder_award_id":"1434401","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6302294139","display_name":null,"funder_award_id":"CMMI-1434401","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6671297155","display_name":null,"funder_award_id":"CAREER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7372974065","display_name":"CI-P: Planning for SMART-MOVE: A Spatiotemporal Annotated Human Activity Repository for Advanced Motion Recognition and Analysis Research","funder_award_id":"1405985","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8238368010","display_name":null,"funder_award_id":"1434401","funder_id":"https://openalex.org/F4320337391","funder_display_name":"Division of Civil, Mechanical and Manufacturing Innovation"},{"id":"https://openalex.org/G8399341322","display_name":"RI: Small: Collaborative Research: A Topological Analysis of Uncertainly Representation in the Brain","funder_award_id":"1718853","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8430772007","display_name":null,"funder_award_id":"IIS-1423056","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G920259479","display_name":null,"funder_award_id":"CNS-1405985","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"},{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2962898908.pdf","grobid_xml":"https://content.openalex.org/works/W2962898908.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W5896900","https://openalex.org/W1480527676","https://openalex.org/W1526543462","https://openalex.org/W1531818640","https://openalex.org/W1809653203","https://openalex.org/W1848652813","https://openalex.org/W1966644764","https://openalex.org/W1987543638","https://openalex.org/W2015251183","https://openalex.org/W2046376809","https://openalex.org/W2054804828","https://openalex.org/W2066153095","https://openalex.org/W2089269329","https://openalex.org/W2106291522","https://openalex.org/W2112420033","https://openalex.org/W2117046315","https://openalex.org/W2121863487","https://openalex.org/W2151976295","https://openalex.org/W2171837816","https://openalex.org/W2185572669","https://openalex.org/W2252409454","https://openalex.org/W2285353291","https://openalex.org/W2295739065","https://openalex.org/W2320605305","https://openalex.org/W2346744086","https://openalex.org/W2398274324","https://openalex.org/W2474213459","https://openalex.org/W2500478584","https://openalex.org/W2525036370","https://openalex.org/W2576014002","https://openalex.org/W2583085944","https://openalex.org/W2586680856","https://openalex.org/W2606868178","https://openalex.org/W2734936460","https://openalex.org/W2749279690","https://openalex.org/W2767518867","https://openalex.org/W2784055555","https://openalex.org/W4234967753","https://openalex.org/W4300369184","https://openalex.org/W6691666647"],"related_works":["https://openalex.org/W3157260717","https://openalex.org/W1989929201","https://openalex.org/W2735645867","https://openalex.org/W2963498005","https://openalex.org/W2328171598","https://openalex.org/W4210372979","https://openalex.org/W4318480255","https://openalex.org/W2806578822","https://openalex.org/W4254922057","https://openalex.org/W2991009317"],"abstract_inverted_index":{"We":[0,116],"consider":[1],"the":[2,7,17,20,34,39,44,56,62,73,82,91,96,99,119,125,163,174],"actor-critic":[3],"contextual":[4,30,58,159],"bandit":[5,31,59,160],"for":[6,33,50],"mobile":[8],"health":[9],"(mHealth)":[10],"intervention.":[11],"State-of-the-art":[12],"decision-making":[13],"algorithms":[14],"generally":[15],"ignore":[16],"outliers":[18,179],"in":[19,95,180],"data-set.":[21],"In":[22],"this":[23],"paper,":[24],"we":[25,105],"propose":[26,106],"a":[27,51,77,136,181],"novel":[28],"robust":[29],"method":[32,79,150],"mHealth.":[35],"It":[36],"can":[37,122,151],"achieve":[38,152],"conflicting":[40],"goal":[41],"of":[42,46,90,139,183],"reducing":[43],"influence":[45],"outliers,":[47,166],"while":[48],"seeking":[49],"similar":[52],"solution":[53],"compared":[54,156],"with":[55,157,178],"state-of-the-art":[57,158,171],"methods":[60,161,172],"on":[61,69,144,162,173],"datasets":[63,146],"without":[64,165],"outliers.":[65],"Such":[66],"performance":[67],"relies":[68],"two":[70,145],"technologies:":[71],"(1)":[72],"capped-L2":[74],"norm;":[75],"(2)":[76],"reliable":[78],"to":[80],"set":[81],"threshold":[83],"hyper-parameter,":[84],"which":[85],"is":[86,101],"inspired":[87],"by":[88],"one":[89],"most":[92],"fundamental":[93],"techniques":[94],"statistics.":[97],"Although":[98],"model":[100],"non-convex":[102],"and":[103,111,132,167],"non-differentiable,":[104],"an":[107],"effective":[108],"reweighted":[109],"algorithm":[110,121],"provide":[112],"solid":[113],"theoretical":[114],"analyses.":[115],"prove":[117],"that":[118,148],"proposed":[120],"sufficiently":[123],"decrease":[124],"objective":[126],"function":[127],"value":[128],"at":[129],"each":[130],"iteration":[131],"will":[133],"converge":[134],"after":[135],"finite":[137],"number":[138],"iterations.":[140],"Extensive":[141],"experiment":[142],"results":[143,155],"demonstrate":[147],"our":[149],"almost":[153],"identical":[154],"dataset":[164,177],"significantly":[168],"outperform":[169],"those":[170],"badly":[175],"noised":[176],"variety":[182],"parameter":[184],"settings.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
