{"id":"https://openalex.org/W4416873225","doi":"https://doi.org/10.1109/tkde.2025.3639070","title":"Locally Differentially Private Truth Discovery for Sparse Crowdsensing","display_name":"Locally Differentially Private Truth Discovery for Sparse Crowdsensing","publication_year":2025,"publication_date":"2025-12-01","ids":{"openalex":"https://openalex.org/W4416873225","doi":"https://doi.org/10.1109/tkde.2025.3639070"},"language":null,"primary_location":{"id":"doi:10.1109/tkde.2025.3639070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3639070","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"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 Knowledge and Data Engineering","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":null,"display_name":"Pengfei Zhang","orcid":"https://orcid.org/0000-0003-0663-332X"},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pengfei Zhang","raw_affiliation_strings":["State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining, School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, China","State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining, the School of Computer Science and Engineering, Anhui University of Science and Technology, Anhui University of Science and Technology, Huainan, China"],"raw_orcid":"https://orcid.org/0000-0003-0663-332X","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining, School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, China","institution_ids":["https://openalex.org/I184681353"]},{"raw_affiliation_string":"State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining, the School of Computer Science and Engineering, Anhui University of Science and Technology, Anhui University of Science and Technology, Huainan, China","institution_ids":["https://openalex.org/I184681353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100746182","display_name":"Zhikun Zhang","orcid":"https://orcid.org/0000-0001-7208-3392"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhikun Zhang","raw_affiliation_strings":["Zhejiang University, Hangzhou, China","Zhejiang University, China"],"raw_orcid":"https://orcid.org/0000-0001-7208-3392","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082946615","display_name":"Yang Cao","orcid":"https://orcid.org/0000-0002-6424-8633"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yang Cao","raw_affiliation_strings":["Tokyo Institute of Technology, Meguro, Japan","Tokyo Institute of Technology, Japan"],"raw_orcid":"https://orcid.org/0000-0002-6424-8633","affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Meguro, Japan","institution_ids":["https://openalex.org/I114531698"]},{"raw_affiliation_string":"Tokyo Institute of Technology, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiang Cheng","orcid":"https://orcid.org/0000-0001-6556-2264"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Cheng","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China","Beijing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0001-6556-2264","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100750950","display_name":"Youwen Zhu","orcid":"https://orcid.org/0000-0003-4365-9713"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youwen Zhu","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics, Nanjing, China","Nanjing University of Aeronautics and Astronautics, China"],"raw_orcid":"https://orcid.org/0000-0003-4365-9713","affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062494507","display_name":"Zhiquan Liu","orcid":"https://orcid.org/0000-0002-3934-2177"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiquan Liu","raw_affiliation_strings":["Jinan University, Guangzhou, China","Jinan University, China"],"raw_orcid":"https://orcid.org/0000-0002-3934-2177","affiliations":[{"raw_affiliation_string":"Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]},{"raw_affiliation_string":"Jinan University, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100705326","display_name":"Ji Zhang","orcid":"https://orcid.org/0000-0001-7167-6970"},"institutions":[{"id":"https://openalex.org/I185523456","display_name":"University of Southern Queensland","ror":"https://ror.org/04sjbnx57","country_code":"AU","type":"education","lineage":["https://openalex.org/I185523456"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ji Zhang","raw_affiliation_strings":["University of Southern Queensland, Toowoomba, Australia","University of Southern Queensland, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern Queensland, Toowoomba, Australia","institution_ids":["https://openalex.org/I185523456"]},{"raw_affiliation_string":"University of Southern Queensland, Australia","institution_ids":["https://openalex.org/I185523456"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I184681353"],"apc_list":null,"apc_paid":null,"fwci":1.3896,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.89380121,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"38","issue":"2","first_page":"1189","last_page":"1205"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social 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":0.7332000136375427},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.4966000020503998},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.492000013589859},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.46950000524520874},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4374000132083893},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.3953999876976013},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.39430001378059387},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.384799987077713},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.3790000081062317}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7985000014305115},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.7332000136375427},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.4966000020503998},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.492000013589859},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.46950000524520874},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4512999951839447},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43970000743865967},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4007999897003174},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3953999876976013},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.39430001378059387},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.384799987077713},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.3790000081062317},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.37290000915527344},{"id":"https://openalex.org/C137822555","wikidata":"https://www.wikidata.org/wiki/Q2587068","display_name":"Information sensitivity","level":2,"score":0.35179999470710754},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.3452000021934509},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.32690000534057617},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.30169999599456787},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30079999566078186},{"id":"https://openalex.org/C183057437","wikidata":"https://www.wikidata.org/wiki/Q671617","display_name":"Laplace distribution","level":3,"score":0.2955000102519989},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.2904999852180481},{"id":"https://openalex.org/C27956954","wikidata":"https://www.wikidata.org/wiki/Q391371","display_name":"Bernoulli distribution","level":3,"score":0.28700000047683716},{"id":"https://openalex.org/C56086750","wikidata":"https://www.wikidata.org/wiki/Q6042592","display_name":"Integer programming","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C152361515","wikidata":"https://www.wikidata.org/wiki/Q181328","display_name":"Bernoulli's principle","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C165700671","wikidata":"https://www.wikidata.org/wiki/Q203484","display_name":"Laplace operator","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C163504300","wikidata":"https://www.wikidata.org/wiki/Q2364925","display_name":"Causal structure","level":2,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2025.3639070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3639070","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4279750524","display_name":null,"funder_award_id":"2024020300","funder_id":"https://openalex.org/F4320312071","funder_display_name":"Ministry of Education, Libya"},{"id":"https://openalex.org/G6533485461","display_name":null,"funder_award_id":"2024PY010","funder_id":"https://openalex.org/F4320312071","funder_display_name":"Ministry of Education, Libya"},{"id":"https://openalex.org/G6562299470","display_name":null,"funder_award_id":"62441618","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7097105892","display_name":null,"funder_award_id":"62402431","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7356091226","display_name":null,"funder_award_id":"62272195","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8029039401","display_name":null,"funder_award_id":"62172216","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8521681689","display_name":null,"funder_award_id":"62372051","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320312071","display_name":"Ministry of Education, Libya","ror":"https://ror.org/02w030k33"},{"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":43,"referenced_works":["https://openalex.org/W2086413055","https://openalex.org/W2785582092","https://openalex.org/W2808769527","https://openalex.org/W2903182593","https://openalex.org/W2930558539","https://openalex.org/W2947538082","https://openalex.org/W2964332492","https://openalex.org/W3036867964","https://openalex.org/W3047069132","https://openalex.org/W3092236496","https://openalex.org/W3112250879","https://openalex.org/W3126717083","https://openalex.org/W3129462373","https://openalex.org/W3133955889","https://openalex.org/W3135807060","https://openalex.org/W3198790660","https://openalex.org/W3201054243","https://openalex.org/W4213021369","https://openalex.org/W4220714137","https://openalex.org/W4285202693","https://openalex.org/W4294707627","https://openalex.org/W4296339010","https://openalex.org/W4308381125","https://openalex.org/W4312083224","https://openalex.org/W4313307295","https://openalex.org/W4315606031","https://openalex.org/W4315630073","https://openalex.org/W4323896432","https://openalex.org/W4323923516","https://openalex.org/W4324284602","https://openalex.org/W4368363113","https://openalex.org/W4377079847","https://openalex.org/W4377081230","https://openalex.org/W4385948635","https://openalex.org/W4389374238","https://openalex.org/W4393184946","https://openalex.org/W4399774107","https://openalex.org/W4403936755","https://openalex.org/W4404370715","https://openalex.org/W4406947279","https://openalex.org/W4408173312","https://openalex.org/W4409581208","https://openalex.org/W4410227771"],"related_works":[],"abstract_inverted_index":{"Truth":[0],"discovery":[1,66,99,143,223,234],"has":[2,25],"emerged":[3,26],"as":[4,27,54],"an":[5],"effective":[6],"tool":[7],"to":[8,64,129,134,169,231],"mitigate":[9],"data":[10,16,138,172],"inconsistency":[11],"in":[12,41,67,103,276],"crowdsensing":[13],"by":[14,144,235,272],"prioritizing":[15],"from":[17,194],"high-quality":[18],"responders.":[19],"While":[20],"local":[21],"differential":[22],"privacy":[23,77,156,257],"(LDP)":[24],"a":[28,38,113,180,200,207,220],"crucial":[29],"privacy-preserving":[30],"paradigm,":[31],"existing":[32],"studies":[33],"under":[34],"LDP":[35,60],"rarely":[36],"explore":[37],"worker's":[39],"participation":[40],"specific":[42],"tasks":[43,160],"for":[44,120],"sparse":[45,68,137,192,208],"scenarios,":[46],"which":[47],"may":[48,70],"also":[49],"reveal":[50],"sensitive":[51],"information":[52],"such":[53],"individual":[55],"preferences":[56],"and":[57,79,97,140,163,205,241,261],"behaviors.":[58],"Existing":[59],"mechanisms,":[61],"when":[62],"applied":[63],"truth":[65,89,98,117,142,222,233],"settings,":[69],"create":[71],"undesirable":[72],"dense":[73],"distributions,":[74],"provide":[75],"insufficient":[76],"protection,":[78],"introduce":[80],"excessive":[81],"noise,":[82,177],"compromising":[83],"the":[84,92,104,136,146,155,159,164,171,191,245,270],"efficacy":[85],"of":[86,149,157,248],"subsequent":[87],"non-private":[88],"discovery.":[90],"Additionally,":[91],"interplay":[93],"between":[94,238],"noise":[95,152],"injection":[96],"remains":[100],"insufficiently":[101],"explored":[102],"current":[105],"literature.":[106],"To":[107,189],"address":[108,170],"these":[109],"issues,":[110],"we":[111,178,198],"propose":[112],"lOcally":[114],"differentially":[115],"private":[116],"diSCovery":[118],"approach":[119],"spArse":[121],"cRowdsensing,":[122],"namely":[123],"OSCAR.":[124],"The":[125],"main":[126],"idea":[127],"is":[128],"use":[130],"advanced":[131],"optimization":[132],"techniques":[133],"reconstruct":[135],"distribution":[139],"re-formalize":[141,232],"considering":[145],"statistical":[147,246],"characteristics":[148],"injected":[150],"Laplacian":[151,249],"while":[153,175],"protecting":[154],"both":[158],"being":[161],"completed":[162],"corresponding":[165],"sensory":[166],"data.":[167],"Specifically,":[168],"density":[173],"concerns":[174],"alleviating":[176],"design":[179],"randomized":[181],"response":[182],"based":[183,213,243],"Bernoulli":[184],"matrix":[185],"factorization":[186],"method":[187,211,224],"BerRR.":[188],"recover":[190],"structures":[193],"densified,":[195],"perturbed":[196],"data,":[197],"formalize":[199],"0-1":[201],"integer":[202],"programming":[203],"problem":[204],"develop":[206],"recovery":[209],"solving":[210],"SpaIE":[212],"on":[214,244],"implicit":[215],"enumeration.":[216],"We":[217],"further":[218],"devise":[219],"Laplacian-sensitive":[221],"LapCRH":[225],"that":[226,267],"leverages":[227],"maximum":[228],"likelihood":[229],"estimation":[230],"measuring":[236],"differences":[237],"noisy":[239],"values":[240],"truths":[242],"characteristic":[247],"noise.":[250],"Our":[251],"comprehensive":[252],"theoretical":[253],"analysis":[254],"establishes":[255],"OSCAR's":[256],"guarantees,":[258],"utility":[259],"bounds,":[260],"computational":[262],"complexity.":[263],"Experimental":[264],"results":[265],"show":[266],"OSCAR":[268],"surpasses":[269],"state-of-the-arts":[271],"at":[273],"least":[274],"30%":[275],"accuracy":[277],"improvement.":[278]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-11T08:15:01.531666","created_date":"2025-12-01T00:00:00"}
