{"id":"https://openalex.org/W4413360901","doi":"https://doi.org/10.1109/icde65448.2025.00161","title":"Towards Learning on Vertically Partitioned Data with Distributed Differential Privacy","display_name":"Towards Learning on Vertically Partitioned Data with Distributed Differential Privacy","publication_year":2025,"publication_date":"2025-05-19","ids":{"openalex":"https://openalex.org/W4413360901","doi":"https://doi.org/10.1109/icde65448.2025.00161"},"language":"en","primary_location":{"id":"doi:10.1109/icde65448.2025.00161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde65448.2025.00161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 41st International Conference on Data Engineering (ICDE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5089624047","display_name":"Ergute Bao","orcid":"https://orcid.org/0000-0002-4438-8065"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ergute Bao","raw_affiliation_strings":["National University of Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111728714","display_name":"Fei Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fei Wei","raw_affiliation_strings":["Alibaba Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba Group","institution_ids":["https://openalex.org/I4210095624"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034022345","display_name":"Yin Yang","orcid":"https://orcid.org/0000-0002-0549-3882"},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Yin Yang","raw_affiliation_strings":["College of Science and Engineering, Hamad Bin Khalifa University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Science and Engineering, Hamad Bin Khalifa University","institution_ids":["https://openalex.org/I4210144839"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010903591","display_name":"Xiaokui Xiao","orcid":"https://orcid.org/0000-0003-0914-4580"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xiaokui Xiao","raw_affiliation_strings":["National University of Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119363275","display_name":"Tianyu Pang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tianyu Pang","raw_affiliation_strings":["SEA AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SEA AI Lab","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101995509","display_name":"Chao Du","orcid":"https://orcid.org/0009-0008-2893-5461"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chao Du","raw_affiliation_strings":["SEA AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SEA AI Lab","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.673,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.84420826,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2121","last_page":"2134"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9980999827384949,"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":0.9980999827384949,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9639999866485596,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11720","display_name":"Probability and Risk Models","score":0.9397000074386597,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.8947535753250122},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7463199496269226},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.48180073499679565},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.22220000624656677},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.18499687314033508}],"concepts":[{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.8947535753250122},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7463199496269226},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.48180073499679565},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.22220000624656677},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.18499687314033508}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icde65448.2025.00161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde65448.2025.00161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 41st International Conference on Data Engineering (ICDE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":76,"referenced_works":["https://openalex.org/W44899178","https://openalex.org/W1485800369","https://openalex.org/W1873763122","https://openalex.org/W1969009977","https://openalex.org/W1981029888","https://openalex.org/W1997690112","https://openalex.org/W2006453614","https://openalex.org/W2009797711","https://openalex.org/W2010523825","https://openalex.org/W2042946599","https://openalex.org/W2047265165","https://openalex.org/W2053637704","https://openalex.org/W2088492763","https://openalex.org/W2093367651","https://openalex.org/W2096870293","https://openalex.org/W2099940443","https://openalex.org/W2110868467","https://openalex.org/W2130099852","https://openalex.org/W2162379889","https://openalex.org/W2165157425","https://openalex.org/W2168190036","https://openalex.org/W2473418344","https://openalex.org/W2534976269","https://openalex.org/W2591882872","https://openalex.org/W2594311007","https://openalex.org/W2701059868","https://openalex.org/W2761138375","https://openalex.org/W2765200655","https://openalex.org/W2767079719","https://openalex.org/W2950321888","https://openalex.org/W2963456518","https://openalex.org/W2963629772","https://openalex.org/W2964117144","https://openalex.org/W2996422317","https://openalex.org/W2997422449","https://openalex.org/W3017915781","https://openalex.org/W3049595782","https://openalex.org/W3085392082","https://openalex.org/W3094542121","https://openalex.org/W3095212288","https://openalex.org/W3096074096","https://openalex.org/W3103312471","https://openalex.org/W3108672920","https://openalex.org/W3173785784","https://openalex.org/W4205228770","https://openalex.org/W4206996002","https://openalex.org/W4226083947","https://openalex.org/W4281848858","https://openalex.org/W4288057725","https://openalex.org/W4288057781","https://openalex.org/W4289446312","https://openalex.org/W4289533960","https://openalex.org/W4294904094","https://openalex.org/W4308633695","https://openalex.org/W4308643126","https://openalex.org/W4312395750","https://openalex.org/W4312646383","https://openalex.org/W4362515174","https://openalex.org/W4380433128","https://openalex.org/W4381328553","https://openalex.org/W4385412524","https://openalex.org/W4385653232","https://openalex.org/W4388131344","https://openalex.org/W4388858046","https://openalex.org/W4391250546","https://openalex.org/W4393180328","https://openalex.org/W4400909528","https://openalex.org/W4400909957","https://openalex.org/W4400910119","https://openalex.org/W4400910164","https://openalex.org/W4400910525","https://openalex.org/W4400977903","https://openalex.org/W4402041878","https://openalex.org/W4402263660","https://openalex.org/W4408060521","https://openalex.org/W4413360901"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3038283795","https://openalex.org/W2604501336","https://openalex.org/W2558166297","https://openalex.org/W2734500670","https://openalex.org/W2315671126","https://openalex.org/W798507144","https://openalex.org/W4391095118"],"abstract_inverted_index":{"Analysis":[0],"of":[1,8,210,219,234,258,272,313],"distributed":[2,239],"data":[3,10,31,64,69,93,157,162,212],"typically":[4],"requires":[5],"the":[6,9,21,24,30,68,83,105,182,211,222,235,238,261,269,283,287,310],"collaboration":[7],"owners,":[11],"as":[12,14,35,78,230],"well":[13],"privacy":[15,109,116,270],"protection.":[16],"This":[17],"paper":[18],"focuses":[19],"on":[20,120,140,207,294,306],"scenario":[22],"where":[23,221],"database":[25],"is":[26,102,279],"vertically":[27],"partitioned":[28],"onto":[29],"owners":[32,70],"(referred":[33],"to":[34,51,55,99,103,124,167,181,202,225,254,281],"vertical":[36],"federated":[37],"learning":[38,216],"or":[39],"VFL),":[40],"e.g.,":[41,155],"an":[42,46,134],"e-commerce":[43],"platform":[44],"and":[45,114,128,214,275,301],"online":[47],"payment":[48],"service":[49],"collaborate":[50],"build":[52],"a":[53,74,194,199,208,231,251],"model":[54,66,85,106,169],"predict":[56],"user":[57],"behavior.":[58],"To":[59],"avoid":[60],"revealing":[61],"their":[62],"private":[63],"during":[65],"fitting,":[67],"commonly":[71],"participate":[72],"in":[73,286],"cryptographic":[75],"protocol":[76],"such":[77],"secure":[79],"multiparty":[80],"computation.":[81],"However,":[82],"resulting":[84],"may":[86],"still":[87],"leak":[88],"sensitive":[89,223],"information":[90,224],"under":[91],"sophisticated":[92],"extraction":[94],"attacks.":[95],"A":[96],"rigorous":[97],"solution":[98,136],"this":[100,190,203,256],"issue":[101],"compute":[104],"with":[107,148,163,178],"differential":[108],"(DP),":[110],"which":[111],"provides":[112],"strong":[113,311],"well-accepted":[115],"guarantees.":[117],"Enforcing":[118],"DP":[119,179,240],"VFL":[121,177],"turns":[122],"out":[123],"be":[125,228],"highly":[126],"challenging,":[127],"there":[129],"does":[130,243],"not":[131,244],"yet":[132],"exist":[133],"effective":[135],"that":[137,242,277],"avoids":[138],"reliance":[139],"any":[141,187,246],"trusted":[142,247],"party.":[143],"Consequently,":[144],"practitioners":[145],"are":[146],"left":[147],"rather":[149],"basic":[150],"approaches":[151],"for":[152,176],"ensuring":[153],"DP,":[154],"each":[156],"owner":[158],"perturbs":[159],"her":[160],"local":[161],"additive":[164],"noises,":[165],"leading":[166],"suboptimal":[168],"utility.":[170],"Can":[171],"we":[172,192,249],"achieve":[173],"privacy-utility":[174,284],"trade-offs":[175,285],"comparable":[180],"centralized":[183,288],"setting,":[184],"without":[185],"trusting":[186],"party?":[188],"In":[189],"paper,":[191],"make":[193],"significant":[195],"step":[196],"towards":[197],"providing":[198],"positive":[200],"answer":[201],"question.":[204],"We":[205,266,290],"focus":[206],"subset":[209],"analysis":[213,300],"machine":[215],"tasks-the":[217],"class":[218,257],"tasks":[220],"release":[226],"can":[227],"expressed":[229],"polynomial":[232],"function":[233],"input.":[236],"Following":[237],"framework":[241],"require":[245],"party,":[248],"propose":[250],"generic":[252],"mechanism":[253],"solve":[255],"problems,":[259],"called":[260],"Skellam":[262],"Quantization":[263],"Mechanism":[264],"(SQM).":[265],"formally":[267],"prove":[268],"guarantee":[271],"our":[273],"solution,":[274],"show":[276],"it":[278],"able":[280],"match":[282],"setting.":[289],"then":[291],"instantiate":[292],"SQM":[293],"two":[295],"classical":[296],"tasks,":[297],"principal":[298],"component":[299],"logistic":[302],"regression.":[303],"Extensive":[304],"experiments":[305],"real-world":[307],"datasets":[308],"confirm":[309],"performance":[312],"SQM.":[314]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}