{"id":"https://openalex.org/W4385568042","doi":"https://doi.org/10.1145/3580305.3599311","title":"DM-PFL: Hitchhiking Generic Federated Learning for Efficient Shift-Robust Personalization","display_name":"DM-PFL: Hitchhiking Generic Federated Learning for Efficient Shift-Robust Personalization","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385568042","doi":"https://doi.org/10.1145/3580305.3599311"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599311","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580305.3599311","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580305.3599311","source":null,"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery 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/10.1145/3580305.3599311","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102979557","display_name":"Wenhao Zhang","orcid":"https://orcid.org/0009-0001-2763-8835"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenhao Zhang","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011140675","display_name":"Zimu Zhou","orcid":"https://orcid.org/0000-0002-5457-6967"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zimu Zhou","raw_affiliation_strings":["City University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101838851","display_name":"Yansheng Wang","orcid":"https://orcid.org/0009-0007-3496-8676"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yansheng Wang","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051874566","display_name":"Yongxin Tong","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongxin Tong","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102979557"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":1.5525,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.86231709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3396","last_page":"3408"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","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/T10764","display_name":"Privacy-Preserving Technologies in Data","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/T10203","display_name":"Recommender Systems and Techniques","score":0.9733999967575073,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9639000296592712,"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/federated-learning","display_name":"Federated learning","score":0.8562339544296265},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8471642732620239},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.7636535167694092},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.744729220867157},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6227667331695557},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.47885891795158386},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.45974546670913696},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39044997096061707},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3690406084060669},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.1273125410079956}],"concepts":[{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.8562339544296265},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8471642732620239},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.7636535167694092},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.744729220867157},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6227667331695557},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.47885891795158386},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.45974546670913696},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39044997096061707},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3690406084060669},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1273125410079956},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3580305.3599311","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580305.3599311","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580305.3599311","source":null,"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3580305.3599311","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580305.3599311","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580305.3599311","source":null,"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4569554029","display_name":null,"funder_award_id":"9610633","funder_id":"https://openalex.org/F4320309893","funder_display_name":"City University of Hong Kong"},{"id":"https://openalex.org/G5944244991","display_name":null,"funder_award_id":"62076017","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8197150722","display_name":null,"funder_award_id":"U21A20516","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8565926968","display_name":null,"funder_award_id":"U21A2051","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309893","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23"},{"id":"https://openalex.org/F4320319065","display_name":"Aromatic Plant Research Center","ror":"https://ror.org/05eebgw43"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321125","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385568042.pdf","grobid_xml":"https://content.openalex.org/works/W4385568042.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W134960717","https://openalex.org/W2112796928","https://openalex.org/W2896422817","https://openalex.org/W2912213068","https://openalex.org/W2995022099","https://openalex.org/W3080934299","https://openalex.org/W3133814152","https://openalex.org/W3153149826","https://openalex.org/W3168256142","https://openalex.org/W3210103168","https://openalex.org/W3214721897","https://openalex.org/W4212774754","https://openalex.org/W4225796852","https://openalex.org/W4288086177","https://openalex.org/W4385573478","https://openalex.org/W6602046083"],"related_works":["https://openalex.org/W2109940557","https://openalex.org/W2466832359","https://openalex.org/W4298221930","https://openalex.org/W3172493050","https://openalex.org/W1582019636","https://openalex.org/W1499005795","https://openalex.org/W2777914285","https://openalex.org/W4303448918","https://openalex.org/W4308945107","https://openalex.org/W4319453716"],"abstract_inverted_index":{"Personalized":[0],"federated":[1,49,65,149],"learning":[2,50,150],"collaboratively":[3],"trains":[4],"client-specific":[5],"models,":[6],"which":[7],"holds":[8],"potential":[9],"for":[10,64],"various":[11,119],"mobile":[12,53],"and":[13,29,32,106,113,142],"IoT":[14],"applications":[15],"with":[16,82,109],"heterogeneous":[17],"data.":[18],"However,":[19],"existing":[20],"solutions":[21],"are":[22],"vulnerable":[23],"to":[24,70,75,102,146],"distribution":[25,135],"shifts":[26,136],"between":[27],"training":[28,35,85],"test":[30,129],"data,":[31],"involve":[33],"high":[34],"workloads":[36],"on":[37,51,118],"local":[38],"devices.":[39],"These":[40],"two":[41],"shortcomings":[42],"hinder":[43],"the":[44,72,77,128,140],"practical":[45],"usage":[46],"of":[47,79,133],"personalized":[48,80,107,148],"real-world":[52],"applications.":[54],"To":[55,87],"overcome":[56],"these":[57],"drawbacks,":[58],"we":[59,90],"explore":[60],"efficient":[61],"shift-robust":[62],"personalization":[63],"learning.":[66],"The":[67],"principle":[68],"is":[69],"hitchhike":[71],"global":[73,105],"model":[74],"improve":[76,127],"shift-robustness":[78],"models":[81,108],"minimal":[83],"extra":[84],"overhead.":[86],"this":[88],"end,":[89],"present":[91],"DM-PFL,":[92],"a":[93,98],"novel":[94],"framework":[95],"that":[96,122],"utilizes":[97],"dual":[99],"masking":[100],"mechanism":[101],"train":[103],"both":[104],"weight-level":[110],"parameter":[111],"sharing":[112],"end-to-end":[114],"sparse":[115],"training.":[116],"Evaluations":[117],"datasets":[120],"show":[121],"our":[123],"methods":[124],"not":[125],"only":[126],"accuracy":[130],"in":[131],"presence":[132],"test-time":[134],"but":[137],"also":[138],"save":[139],"communication":[141],"computation":[143],"costs":[144],"compared":[145],"state-of-the-art":[147],"schemes.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}