{"id":"https://openalex.org/W4402780394","doi":"https://doi.org/10.1109/tpami.2024.3457751","title":"Federated Feature Augmentation and Alignment","display_name":"Federated Feature Augmentation and Alignment","publication_year":2024,"publication_date":"2024-09-16","ids":{"openalex":"https://openalex.org/W4402780394","doi":"https://doi.org/10.1109/tpami.2024.3457751"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2024.3457751","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3457751","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-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/A5091518967","display_name":"Tianfei Zhou","orcid":"https://orcid.org/0000-0001-5475-1473"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianfei Zhou","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China","Beijing Institute of Technology, China"],"raw_orcid":"https://orcid.org/0000-0001-5475-1473","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014346487","display_name":"Ye Yuan","orcid":"https://orcid.org/0000-0002-0247-9866"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Yuan","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China","Beijing Institute of Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-0247-9866","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043220498","display_name":"Binglu Wang","orcid":"https://orcid.org/0000-0002-9266-4685"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binglu Wang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China","Beijing Institute of Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-9266-4685","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102938575","display_name":"Ender Konukoglu","orcid":"https://orcid.org/0000-0003-4152-1323"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Ender Konukoglu","raw_affiliation_strings":["Computer Vision Lab, ETH Zurich, Z&#x00FC;rich, Switzerland","Computer Vision Lab, ETH Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision Lab, ETH Zurich, Z&#x00FC;rich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"Computer Vision Lab, ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2481,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.89400608,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"46","issue":"12","first_page":"11119","last_page":"11135"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.8299999833106995,"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"}},"topics":[{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.8299999833106995,"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/T11448","display_name":"Face recognition and analysis","score":0.7949000000953674,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.7879999876022339,"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":0.6468452215194702},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6292023062705994},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.537992537021637},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4322466254234314},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4245375692844391},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41038841009140015}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6468452215194702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6292023062705994},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.537992537021637},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4322466254234314},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4245375692844391},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41038841009140015},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tpami.2024.3457751","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3457751","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G377220362","display_name":null,"funder_award_id":"62225203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4223126646","display_name":"\u5e94\u7528\u9a71\u52a8\u7684\u5927\u56fe\u6570\u636e\u5efa\u6a21\u7406\u8bba\u4e0e\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61932004","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"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":112,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1678889691","https://openalex.org/W1722318740","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2031342017","https://openalex.org/W2053637704","https://openalex.org/W2074466695","https://openalex.org/W2102909657","https://openalex.org/W2111406701","https://openalex.org/W2149466042","https://openalex.org/W2194775991","https://openalex.org/W2535838896","https://openalex.org/W2551176409","https://openalex.org/W2603777577","https://openalex.org/W2618530766","https://openalex.org/W2734358244","https://openalex.org/W2763549966","https://openalex.org/W2766151966","https://openalex.org/W2798658180","https://openalex.org/W2930926105","https://openalex.org/W2963043696","https://openalex.org/W2963446712","https://openalex.org/W2963952467","https://openalex.org/W2970408908","https://openalex.org/W2979766322","https://openalex.org/W2981720610","https://openalex.org/W2992308087","https://openalex.org/W2995022099","https://openalex.org/W3004531689","https://openalex.org/W3012501605","https://openalex.org/W3021654819","https://openalex.org/W3095569631","https://openalex.org/W3103989228","https://openalex.org/W3107100345","https://openalex.org/W3133542152","https://openalex.org/W3138516171","https://openalex.org/W3168256142","https://openalex.org/W3169044395","https://openalex.org/W3182158470","https://openalex.org/W3185864054","https://openalex.org/W3202544039","https://openalex.org/W4214611271","https://openalex.org/W4225978071","https://openalex.org/W4226158211","https://openalex.org/W4226461837","https://openalex.org/W4283796083","https://openalex.org/W4285184341","https://openalex.org/W4289639938","https://openalex.org/W4312365264","https://openalex.org/W4312465577","https://openalex.org/W4312517097","https://openalex.org/W4312869277","https://openalex.org/W4313023122","https://openalex.org/W4319300240","https://openalex.org/W4320015877","https://openalex.org/W4367663293","https://openalex.org/W4385453029","https://openalex.org/W4386065428","https://openalex.org/W4386066070","https://openalex.org/W4386066134","https://openalex.org/W4386076561","https://openalex.org/W4386083053","https://openalex.org/W4387303319","https://openalex.org/W4389990166","https://openalex.org/W4392024636","https://openalex.org/W4394677290","https://openalex.org/W4402702992","https://openalex.org/W6629606793","https://openalex.org/W6634343353","https://openalex.org/W6640963894","https://openalex.org/W6678977525","https://openalex.org/W6682208247","https://openalex.org/W6683124652","https://openalex.org/W6728757088","https://openalex.org/W6745136726","https://openalex.org/W6752497734","https://openalex.org/W6754038005","https://openalex.org/W6758684365","https://openalex.org/W6759238902","https://openalex.org/W6760184523","https://openalex.org/W6765939562","https://openalex.org/W6767676916","https://openalex.org/W6767680423","https://openalex.org/W6772307254","https://openalex.org/W6773039429","https://openalex.org/W6773817997","https://openalex.org/W6773976177","https://openalex.org/W6778102432","https://openalex.org/W6779468803","https://openalex.org/W6780679200","https://openalex.org/W6781318954","https://openalex.org/W6782317661","https://openalex.org/W6783600611","https://openalex.org/W6787972765","https://openalex.org/W6789100154","https://openalex.org/W6789305514","https://openalex.org/W6789380839","https://openalex.org/W6790034021","https://openalex.org/W6802035071","https://openalex.org/W6803344470","https://openalex.org/W6803730191","https://openalex.org/W6810790459","https://openalex.org/W6843355076","https://openalex.org/W6845589855","https://openalex.org/W6848993857","https://openalex.org/W6849629322","https://openalex.org/W6849730732","https://openalex.org/W6850488842","https://openalex.org/W6852720851","https://openalex.org/W6854708048","https://openalex.org/W7028611299"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Federated":[0],"learning":[1,14,56],"is":[2,50,102,129,194,203,295],"a":[3,53,68,91,105,149,172,198,237,251],"distributed":[4,28],"paradigm":[5],"that":[6,108,244],"allows":[7],"multiple":[8],"parties":[9],"to":[10,51,58,131,145,164,179,191,249,269,324],"collaboratively":[11],"train":[12],"deep":[13],"models":[15],"without":[16],"direct":[17],"exchange":[18],"of":[19,31,40,47,70,124,152,197,213,229,255,263,328],"raw":[20],"data.":[21],"Nevertheless,":[22],"the":[23,41,142,153,176,180,184,187,195,326,329],"inherent":[24],"non-independent":[25],"and":[26,121,127,183,259,278,302,310],"identically":[27],"(non-i.i.d.)":[29],"nature":[30],"data":[32,111,212],"distribution":[33,112,155,258],"among":[34],"clients":[35,147,268],"results":[36],"in":[37,62,76,141,232,266],"significant":[38],"degradation":[39],"acquired":[42],"model.":[43],"The":[44],"primary":[45],"goal":[46],"this":[48,81,160],"study":[49],"develop":[52],"robust":[54],"federated":[55,86,98,238],"algorithm":[57],"address":[59],"<i>feature":[60],"shift</i>":[61],"clients\u2019":[63],"samples,":[64],"potentially":[65],"arising":[66],"from":[67],"range":[69],"factors":[71],"such":[72],"as":[73,318,320],"acquisition":[74],"discrepancies":[75],"medical":[77],"imaging.":[78],"To":[79],"reach":[80],"goal,":[82],"we":[83,162,235],"first":[84],"propose":[85,163,236],"feature":[87,93,168,220,239,247,257,273],"augmentation":[88,94,188],"(<small>FedFA</small><inline-formula><tex-math":[89,242],"notation=\"LaTeX\">$^{l}$</tex-math></inline-formula>),":[90],"novel":[92],"technique":[95],"tailored":[96],"for":[97],"learning.":[99,274],"<small>FedFA</small><inline-formula><tex-math":[100,192,233,276,279],"notation=\"LaTeX\">$^{l}$</tex-math></inline-formula>":[101,193,277],"based":[103,138,170],"on":[104,139,159,171],"crucial":[106],"insight":[107],"each":[109,166,214],"client's":[110],"can":[113,303],"be":[114,304],"characterized":[115],"by":[116,205,223],"first-/second-order":[117],"statistics":[118,135,221,231,248],"(<i>a.k.a.</i>,":[119],"mean":[120,177],"standard":[122],"deviation)":[123],"latent":[125],"features;":[126],"it":[128],"feasible":[130],"manipulate":[132],"these":[133],"local":[134,167,256],"<i>globally</i>,":[136],"i.e.,":[137],"information":[140],"entire":[143],"federation,":[144],"let":[146],"have":[148],"better":[150],"sense":[151],"global":[154],"across":[156],"clients.":[157,226],"Grounded":[158],"insight,":[161],"augment":[165],"statistic":[169],"normal":[173],"distribution,":[174],"wherein":[175],"corresponds":[178],"original":[181],"statistic,":[182],"variance":[185],"defines":[186],"scope.":[189],"Central":[190],"determination":[196],"meaningful":[199],"Gaussian":[200],"variance,":[201],"which":[202],"accomplished":[204],"taking":[206],"into":[207,307],"account":[208],"not":[209],"only":[210],"biased":[211],"individual":[215],"client,":[216],"but":[217],"also":[218],"underlying":[219],"represented":[222],"all":[224],"participating":[225],"Beyond":[227],"consideration":[228],"<i>low-order</i>":[230],"notation=\"LaTeX\">$^{l}$</tex-math></inline-formula>,":[234],"alignment":[240,262],"component":[241],"notation=\"LaTeX\">$^{h}$</tex-math></inline-formula>)":[243],"exploits":[245],"<i>higher-order</i>":[246],"gain":[250],"more":[252,271],"detailed":[253],"understanding":[254],"enables":[260],"explicit":[261],"augmented":[264],"features":[265],"different":[267],"promote":[270],"consistent":[272],"Combining":[275],"notation=\"LaTeX\">$^{h}$</tex-math></inline-formula>":[280],"yields":[281],"our":[282],"full":[283],"approach":[284],"<small><b>FedFA<inline-formula><tex-math":[285],"notation=\"LaTeX\">$+$</tex-math><alternatives><mml:math":[286,291],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mo>+</mml:mo></mml:math><inline-graphic":[287,292],"xlink:href=\"yuan-ieq8-3457751.gif\"":[288],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"/></alternatives></inline-formula></b></small>.":[289],"<small>FedFA<inline-formula><tex-math":[290],"xlink:href=\"yuan-ieq9-3457751.gif\"":[293],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"/></alternatives></inline-formula></small>":[294],"non-parametric,":[296],"incurs":[297],"negligible":[298],"additional":[299],"communication":[300],"costs,":[301],"seamlessly":[305],"incorporated":[306],"popular":[308],"CNN":[309],"Transformer":[311],"architectures.":[312],"We":[313],"offer":[314],"rigorous":[315],"theoretical":[316],"analysis,":[317],"well":[319],"extensive":[321],"empirical":[322],"justifications":[323],"demonstrate":[325],"effectiveness":[327],"algorithm.":[330]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":7}],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}