{"id":"https://openalex.org/W4224326793","doi":"https://doi.org/10.1145/3485447.3512220","title":"Compressive Sensing Approaches for Sparse Distribution Estimation Under Local Privacy","display_name":"Compressive Sensing Approaches for Sparse Distribution Estimation Under Local Privacy","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4224326793","doi":"https://doi.org/10.1145/3485447.3512220"},"language":"en","primary_location":{"id":"doi:10.1145/3485447.3512220","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512220","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-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/A5079126936","display_name":"Zhongzheng Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhongzheng Xiong","raw_affiliation_strings":["School of Data Science, Fudan University, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100510501","display_name":"Jialin Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jialin Sun","raw_affiliation_strings":["School of Data Science, Fudan University, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084376945","display_name":"Xiaojun Mao","orcid":"https://orcid.org/0000-0002-9362-508X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojun Mao","raw_affiliation_strings":["School of Mathematical Sciences, Shanghai Jiao Tong University, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100370563","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0003-2909-5456"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["School of Data Science, Fudan University, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102004349","display_name":"Ying Shan","orcid":"https://orcid.org/0000-0001-7673-8325"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Shan","raw_affiliation_strings":["Tencent, China"],"affiliations":[{"raw_affiliation_string":"Tencent, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062549536","display_name":"Zengfeng Huang","orcid":"https://orcid.org/0000-0003-2671-7483"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zengfeng Huang","raw_affiliation_strings":["School of Data Science, Fudan University, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5079126936"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.4127,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64098074,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"599","last_page":"609"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9993000030517578,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.6920833587646484},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6726996898651123},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5013673305511475},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4349684417247772},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36571013927459717},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12897741794586182},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10536107420921326}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6920833587646484},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6726996898651123},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5013673305511475},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4349684417247772},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36571013927459717},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12897741794586182},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10536107420921326},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3485447.3512220","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512220","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1872473787","https://openalex.org/W1981029888","https://openalex.org/W2000150201","https://openalex.org/W2001380973","https://openalex.org/W2013823004","https://openalex.org/W2030449718","https://openalex.org/W2053801139","https://openalex.org/W2116148865","https://openalex.org/W2129131372","https://openalex.org/W2145096794","https://openalex.org/W2516766389","https://openalex.org/W2792817205","https://openalex.org/W2963424903","https://openalex.org/W2964138696","https://openalex.org/W2964225095","https://openalex.org/W3109664139","https://openalex.org/W4205228770","https://openalex.org/W4250955649","https://openalex.org/W4302561155"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W1976264255","https://openalex.org/W2358292267"],"abstract_inverted_index":{"Recent":[0],"years,":[1],"local":[2,41,67],"differential":[3,42],"privacy":[4,43,147],"(LDP)":[5],"has":[6,132],"been":[7,133],"adopted":[8],"by":[9],"many":[10],"web":[11],"service":[12],"providers":[13],"like":[14],"Google":[15],"[23],":[16],"Apple":[17],"[33]":[18],"and":[19,24,62,118,144,165,168,172],"Microsoft":[20],"[15]":[21],"to":[22,92],"collect":[23],"analyse":[25],"users\u2019":[26],"data":[27],"privately.":[28],"In":[29,65,105],"this":[30,106],"paper,":[31,107],"we":[32,108],"consider":[33,109,140],"the":[34,50,66,84,93,96,121,145],"problem":[35,131],"of":[36,49,95,123],"discrete":[37],"distribution":[38],"estimation":[39,46,53],"under":[40],"constraints.":[44],"Distribution":[45],"is":[47,56,90],"one":[48],"most":[51],"fundamental":[52],"problems,":[54],"which":[55,99],"widely":[57],"studied":[58,134],"in":[59,83,103],"both":[60],"non-private":[61],"private":[63,69],"settings.":[64],"model,":[68],"mechanisms":[70,153],"with":[71],"provably":[72],"optimal":[73,81,170],"sample":[74,88,171],"complexity":[75,89],"are":[76,80],"known.":[77],"However,":[78],"they":[79,138],"only":[82,139],"worst-case":[85],"sense;":[86],"their":[87],"proportional":[91],"size":[94],"entire":[97],"universe,":[98],"could":[100,126],"be":[101,127],"huge":[102],"practice.":[104],"sparse":[110,113,142,163],"or":[111],"approximately":[112,162],"(e.g.":[114],"highly":[115],"skewed)":[116],"distribution,":[117],"show":[119],"that":[120],"number":[122],"samples":[124],"needed":[125],"significantly":[128],"reduced.":[129],"This":[130],"recently":[135],"[1],":[136],"but":[137],"strict":[141],"distributions":[143,164],"high":[146],"regime.":[148],"We":[149],"propose":[150],"new":[151],"privatization":[152],"based":[154],"on":[155],"compressive":[156],"sensing.":[157],"Our":[158],"methods":[159],"work":[160],"for":[161],"medium":[166],"privacy,":[167],"have":[169],"communication":[173],"complexity.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}