{"id":"https://openalex.org/W7131376661","doi":"https://doi.org/10.1109/icdm65498.2025.00049","title":"Fast Sampling for Privacy-Preserving Lazy Multiplicative Weight Update","display_name":"Fast Sampling for Privacy-Preserving Lazy Multiplicative Weight Update","publication_year":2025,"publication_date":"2025-11-12","ids":{"openalex":"https://openalex.org/W7131376661","doi":"https://doi.org/10.1109/icdm65498.2025.00049"},"language":null,"primary_location":{"id":"doi:10.1109/icdm65498.2025.00049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm65498.2025.00049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Data Mining (ICDM)","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/A5083084103","display_name":"Xiaoyu Li","orcid":"https://orcid.org/0009-0007-3006-3060"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoyu Li","raw_affiliation_strings":["Stevens Institute of Technology,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stevens Institute of Technology,United States","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122093913","display_name":"Zhao Song","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhao Song","raw_affiliation_strings":["University of California,Berkeley,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Berkeley,United States","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125544387","display_name":"Jiale Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiale Zhao","raw_affiliation_strings":["Guangdong University of Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology,China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"417","last_page":"426"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.8169999718666077,"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":0.8169999718666077,"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/T10237","display_name":"Cryptography and Data Security","score":0.037300001829862595,"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/T11719","display_name":"Data Quality and Management","score":0.03060000017285347,"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/multiplicative-function","display_name":"Multiplicative function","score":0.8773999810218811},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.678600013256073},{"id":"https://openalex.org/keywords/sublinear-function","display_name":"Sublinear function","score":0.5529000163078308},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4357999861240387},{"id":"https://openalex.org/keywords/efficient-algorithm","display_name":"Efficient algorithm","score":0.3732999861240387},{"id":"https://openalex.org/keywords/differential","display_name":"Differential (mechanical device)","score":0.3402000069618225},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.31349998712539673}],"concepts":[{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.8773999810218811},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.678600013256073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6141999959945679},{"id":"https://openalex.org/C117160843","wikidata":"https://www.wikidata.org/wiki/Q338652","display_name":"Sublinear function","level":2,"score":0.5529000163078308},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47679999470710754},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4357999861240387},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4244000017642975},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3930000066757202},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.3732999861240387},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33640000224113464},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33469998836517334},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C28901747","wikidata":"https://www.wikidata.org/wiki/Q177571","display_name":"Decision theory","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.25220000743865967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdm65498.2025.00049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm65498.2025.00049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Data Mining (ICDM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1493802692","https://openalex.org/W1873763122","https://openalex.org/W1891810191","https://openalex.org/W1966271560","https://openalex.org/W1968886089","https://openalex.org/W1974033543","https://openalex.org/W1979255915","https://openalex.org/W1982682305","https://openalex.org/W1985310469","https://openalex.org/W1988790447","https://openalex.org/W2014318353","https://openalex.org/W2017851434","https://openalex.org/W2018287013","https://openalex.org/W2035442052","https://openalex.org/W2036940992","https://openalex.org/W2063147436","https://openalex.org/W2063301486","https://openalex.org/W2084224084","https://openalex.org/W2101043704","https://openalex.org/W2106887613","https://openalex.org/W2112420033","https://openalex.org/W2121689290","https://openalex.org/W2123080720","https://openalex.org/W2126700562","https://openalex.org/W2128085284","https://openalex.org/W2133531097","https://openalex.org/W2146897752","https://openalex.org/W2147717514","https://openalex.org/W2150865801","https://openalex.org/W2152402969","https://openalex.org/W2154829922","https://openalex.org/W2162006472","https://openalex.org/W2167139585","https://openalex.org/W2201600774","https://openalex.org/W2260613758","https://openalex.org/W2279901945","https://openalex.org/W2408897693","https://openalex.org/W2508919161","https://openalex.org/W2547958265","https://openalex.org/W2609713339","https://openalex.org/W2742000570","https://openalex.org/W2777981994","https://openalex.org/W2790607499","https://openalex.org/W2952460245","https://openalex.org/W2963266994","https://openalex.org/W2963677907","https://openalex.org/W2979473749","https://openalex.org/W3034220602","https://openalex.org/W3034810578","https://openalex.org/W3034984817","https://openalex.org/W3118621910","https://openalex.org/W3126188815","https://openalex.org/W3135347465","https://openalex.org/W3175970883","https://openalex.org/W3204370728","https://openalex.org/W4205228770","https://openalex.org/W4230281099","https://openalex.org/W4313227168","https://openalex.org/W4321448320","https://openalex.org/W4385187849","https://openalex.org/W4385245566","https://openalex.org/W4390575863","https://openalex.org/W4391107696","https://openalex.org/W4393157395","https://openalex.org/W4409262403"],"related_works":[],"abstract_inverted_index":{"The":[0],"multiplicative":[1,67],"weight":[2,68],"update":[3,69],"method":[4],"is":[5,49],"a":[6,30],"well-known":[7],"algorithm":[8,27],"commonly":[9],"used":[10],"for":[11,82],"decision":[12,108],"making":[13],"based":[14],"on":[15,38,99],"recommendations":[16],"from":[17,29],"n":[18],"experts.":[19],"Despite":[20],"being":[21],"widely":[22],"used,":[23],"the":[24,60,66],"classical":[25],"MWU":[26],"suffers":[28],"linear":[31],"runtime":[32],"complexity,":[33],"which":[34],"limits":[35],"its":[36],"efficiency":[37,81,91],"large":[39],"problems.":[40,84],"Additionally,":[41],"since":[42],"expert":[43],"data":[44,62,86],"may":[45],"be":[46],"sensitive,":[47],"it":[48],"important":[50],"to":[51],"develop":[52],"privacy-preserving":[53],"methods.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58],"propose":[59],"first":[61],"structure":[63,87],"that":[64],"approximates":[65],"in":[70],"sublinear":[71],"time":[72],"(o(n))":[73],"while":[74],"providing":[75],"differential":[76],"privacy":[77,94],"guarantees,":[78],"significantly":[79],"improving":[80],"large-scale":[83],"Our":[85],"both":[88,100],"enhances":[89],"computational":[90],"and":[92,102,106],"ensures":[93],"protection,":[95],"with":[96],"theoretical":[97],"guarantees":[98],"utility":[101],"privacy,":[103],"enabling":[104],"fast":[105],"private":[107],"making.":[109]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-02-26T00:00:00"}