{"id":"https://openalex.org/W2964834134","doi":"https://doi.org/10.24963/ijcai.2019/665","title":"Lower Bound of Locally Differentially Private Sparse Covariance Matrix Estimation","display_name":"Lower Bound of Locally Differentially Private Sparse Covariance Matrix Estimation","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2964834134","doi":"https://doi.org/10.24963/ijcai.2019/665","mag":"2964834134"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/665","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/665","pdf_url":"https://www.ijcai.org/proceedings/2019/0665.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0665.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100401482","display_name":"Di Wang","orcid":"https://orcid.org/0000-0003-4908-0243"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Di Wang","raw_affiliation_strings":["Department of Computer Science and EngineeringState University of New York at Buffalo, NY, USA","Department of Computer Science and Engineering State University of New York at Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and EngineeringState University of New York at Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"Department of Computer Science and Engineering State University of New York at Buffalo, NY, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006945148","display_name":"Jinhui Xu","orcid":"https://orcid.org/0000-0001-5730-9429"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jinhui Xu","raw_affiliation_strings":["Department of Computer Science and EngineeringState University of New York at Buffalo, NY, USA","Department of Computer Science and Engineering State University of New York at Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and EngineeringState University of New York at Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"Department of Computer Science and Engineering State University of New York at Buffalo, NY, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006945148"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":0.7225,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78655121,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4788","last_page":"4794"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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":0.9998999834060669,"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/T11716","display_name":"Random Matrices and Applications","score":0.9951000213623047,"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/T10237","display_name":"Cryptography and Data Security","score":0.9860000014305115,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.8167010545730591},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.7768814563751221},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.6987850666046143},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6346956491470337},{"id":"https://openalex.org/keywords/lemma","display_name":"Lemma (botany)","score":0.6122340559959412},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.5667502284049988},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.558525025844574},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.5556445717811584},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5534374117851257},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5059940218925476},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4363344609737396},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.4208759665489197},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4141785800457001},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3872471749782562},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3767581582069397},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.3513551950454712},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.323822021484375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.27373456954956055},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22608888149261475},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11210733652114868},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.09969723224639893}],"concepts":[{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.8167010545730591},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.7768814563751221},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.6987850666046143},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6346956491470337},{"id":"https://openalex.org/C2777759810","wikidata":"https://www.wikidata.org/wiki/Q149316","display_name":"Lemma (botany)","level":3,"score":0.6122340559959412},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.5667502284049988},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.558525025844574},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.5556445717811584},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5534374117851257},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5059940218925476},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4363344609737396},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.4208759665489197},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4141785800457001},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3872471749782562},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3767581582069397},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.3513551950454712},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.323822021484375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.27373456954956055},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22608888149261475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11210733652114868},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.09969723224639893},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C46757340","wikidata":"https://www.wikidata.org/wiki/Q43238","display_name":"Poaceae","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/665","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/665","pdf_url":"https://www.ijcai.org/proceedings/2019/0665.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/665","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/665","pdf_url":"https://www.ijcai.org/proceedings/2019/0665.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5150152595","display_name":null,"funder_award_id":"CCF-1716400","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8521929477","display_name":"AF:Small: Novel Geometric Techniques for Several Biomedical Problems","funder_award_id":"1716400","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320334164","display_name":"Simons Institute for the Theory of Computing, University of California Berkeley","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964834134.pdf","grobid_xml":"https://content.openalex.org/works/W2964834134.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1509689762","https://openalex.org/W1511694993","https://openalex.org/W1560153690","https://openalex.org/W1862068047","https://openalex.org/W1873763122","https://openalex.org/W1981029888","https://openalex.org/W2004915866","https://openalex.org/W2608195534","https://openalex.org/W2751484150","https://openalex.org/W2787222147","https://openalex.org/W2792817205","https://openalex.org/W2798800923","https://openalex.org/W2799223421","https://openalex.org/W2900759811","https://openalex.org/W2901628803","https://openalex.org/W2902028428","https://openalex.org/W2913871832","https://openalex.org/W2914626004","https://openalex.org/W2952957879","https://openalex.org/W2963881987","https://openalex.org/W3099324314","https://openalex.org/W3107031453","https://openalex.org/W3134875073","https://openalex.org/W4294092623","https://openalex.org/W4392594673"],"related_works":["https://openalex.org/W3038283795","https://openalex.org/W2604501336","https://openalex.org/W2734500670","https://openalex.org/W2965783911","https://openalex.org/W4287250861","https://openalex.org/W2901628803","https://openalex.org/W4367365821","https://openalex.org/W4297810812","https://openalex.org/W4389057959","https://openalex.org/W2028568336"],"abstract_inverted_index":{"In":[0],"this":[1,57],"paper,":[2],"we":[3],"study":[4],"the":[5,12,24,30,39,75,90],"sparse":[6],"covariance":[7],"matrix":[8],"estimation":[9,96],"problem":[10],"in":[11,29],"local":[13],"differential":[14],"privacy":[15],"model,":[16],"and":[17,80],"give":[18],"a":[19,48,61,71,85],"non-trivial":[20],"lower":[21,40,58],"bound":[22,41,59],"on":[23],"non-interactive":[25],"private":[26,77,91],"minimax":[27,92],"risk":[28,93],"metric":[31],"of":[32,74,94],"squared":[33],"spectral":[34],"norm.":[35],"We":[36],"show":[37],"that":[38],"is":[42,60,70],"actually":[43],"tight,":[44],"as":[45,84],"it":[46],"matches":[47],"previous":[49,76],"upper":[50],"bound.":[51],"Our":[52],"main":[53],"technique":[54],"for":[55,88],"achieving":[56],"general":[62,86],"framework,":[63],"called":[64],"General":[65],"Private":[66],"Assouad":[67,78],"Lemma,":[68],"which":[69],"considerable":[72],"generalization":[73],"lemma":[79],"can":[81],"be":[82],"used":[83],"method":[87],"bounding":[89],"matrix-related":[95],"problems.":[97]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
