{"id":"https://openalex.org/W2520789275","doi":"https://doi.org/10.1109/tit.2018.2810313","title":"Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation","display_name":"Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation","publication_year":2018,"publication_date":"2018-03-07","ids":{"openalex":"https://openalex.org/W2520789275","doi":"https://doi.org/10.1109/tit.2018.2810313","mag":"2520789275"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2018.2810313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2018.2810313","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Information Theory","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1609.02208","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079380666","display_name":"Weihao Gao","orcid":"https://orcid.org/0000-0002-5322-7730"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weihao Gao","raw_affiliation_strings":["Department of Electrical and Computer Engineering and Coordinated Science Laboratory, University of Illinois at Urbana\u2013Champaign, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and Coordinated Science Laboratory, University of Illinois at Urbana\u2013Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028243041","display_name":"Sewoong Oh","orcid":"https://orcid.org/0000-0002-8975-8306"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sewoong Oh","raw_affiliation_strings":["Department of Industrial and Enterprise Systems Engineering and Coordinated Science Laboratory, University of Illinois at Urbana\u2013Champaign, IL, USA"],"raw_orcid":"https://orcid.org/0000-0002-8975-8306","affiliations":[{"raw_affiliation_string":"Department of Industrial and Enterprise Systems Engineering and Coordinated Science Laboratory, University of Illinois at Urbana\u2013Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053980484","display_name":"Pramod Viswanath","orcid":"https://orcid.org/0000-0003-3171-8667"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pramod Viswanath","raw_affiliation_strings":["Department of Electrical and Computer Engineering and Coordinated Science Laboratory, University of Illinois at Urbana\u2013Champaign, IL, USA"],"raw_orcid":"https://orcid.org/0000-0003-3171-8667","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and Coordinated Science Laboratory, University of Illinois at Urbana\u2013Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.8434,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.72775546,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"64","issue":"5","first_page":"3313","last_page":"3330"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.996399998664856,"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"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.996399998664856,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9742000102996826,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9696000218391418,"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/estimator","display_name":"Estimator","score":0.8226287364959717},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.6583085060119629},{"id":"https://openalex.org/keywords/entropy-estimation","display_name":"Entropy estimation","score":0.6440982818603516},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6172664165496826},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.613821268081665},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.5129854083061218},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.49008357524871826},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.48693525791168213},{"id":"https://openalex.org/keywords/information-theory","display_name":"Information theory","score":0.47807884216308594},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47741878032684326},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4690419137477875},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.4610532820224762},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36533862352371216},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35010015964508057},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.3474915027618408},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2726735472679138},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23412486910820007},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09059658646583557},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08558952808380127}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8226287364959717},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.6583085060119629},{"id":"https://openalex.org/C95546049","wikidata":"https://www.wikidata.org/wiki/Q1345207","display_name":"Entropy estimation","level":3,"score":0.6440982818603516},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6172664165496826},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.613821268081665},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.5129854083061218},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.49008357524871826},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.48693525791168213},{"id":"https://openalex.org/C52622258","wikidata":"https://www.wikidata.org/wiki/Q131222","display_name":"Information theory","level":2,"score":0.47807884216308594},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47741878032684326},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4690419137477875},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.4610532820224762},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36533862352371216},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35010015964508057},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.3474915027618408},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2726735472679138},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23412486910820007},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09059658646583557},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08558952808380127},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tit.2018.2810313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2018.2810313","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Information Theory","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1609.02208","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1609.02208","pdf_url":"https://arxiv.org/pdf/1609.02208","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2520789275","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1609.02208.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1609.02208","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1609.02208","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1609.02208","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1609.02208","pdf_url":"https://arxiv.org/pdf/1609.02208","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1981050900","https://openalex.org/W1995514448","https://openalex.org/W2004945083","https://openalex.org/W2005560667","https://openalex.org/W2011133724","https://openalex.org/W2016552385","https://openalex.org/W2017823450","https://openalex.org/W2021119035","https://openalex.org/W2022259473","https://openalex.org/W2029140344","https://openalex.org/W2070204917","https://openalex.org/W2070276049","https://openalex.org/W2079296583","https://openalex.org/W2089943482","https://openalex.org/W2092939357","https://openalex.org/W2095324495","https://openalex.org/W2109433950","https://openalex.org/W2144938562","https://openalex.org/W2150879893","https://openalex.org/W2154615866","https://openalex.org/W2165700458","https://openalex.org/W2206302789","https://openalex.org/W2963113682","https://openalex.org/W4213009331","https://openalex.org/W4252979015","https://openalex.org/W6680435774","https://openalex.org/W6680940449","https://openalex.org/W6681504830","https://openalex.org/W6681645814","https://openalex.org/W6686876975","https://openalex.org/W6694831831"],"related_works":["https://openalex.org/W2798473808","https://openalex.org/W2002499739","https://openalex.org/W2054067895","https://openalex.org/W1575590565","https://openalex.org/W2092813355","https://openalex.org/W2898674840","https://openalex.org/W2066079011","https://openalex.org/W2339185677","https://openalex.org/W2807976428","https://openalex.org/W39904068","https://openalex.org/W3106022083","https://openalex.org/W3099611060","https://openalex.org/W2747088508","https://openalex.org/W32343552","https://openalex.org/W3109778503","https://openalex.org/W3122092251","https://openalex.org/W2971322685","https://openalex.org/W3035774392","https://openalex.org/W2181718099","https://openalex.org/W2963482694"],"abstract_inverted_index":{"Estimators":[0],"of":[1,51,67,77,116,125,147,163,170],"information":[2,55],"theoretic":[3],"measures,":[4],"such":[5],"as":[6],"entropy":[7,52],"and":[8,53,84,91,134,152],"mutual":[9,54],"information,":[10],"are":[11],"a":[12,35,72,82,102,107,140,144],"basic":[13],"workhorse":[14],"for":[15],"many":[16],"downstream":[17],"applications":[18],"in":[19,94],"modern":[20],"data":[21,85],"science.":[22],"State-of-the-art":[23],"approaches":[24,46],"have":[25],"been":[26],"either":[27],"geometric":[28],"[nearest":[29],"neighbor":[30],"(NN)-based]":[31],"or":[32],"kernel-based":[33],"(with":[34],"globally":[36],"chosen":[37],"bandwidth).":[38],"In":[39],"this":[40],"paper,":[41],"we":[42,142],"combine":[43],"both":[44,149],"these":[45],"to":[47,106,166],"design":[48],"new":[49],"estimators":[50],"that":[56,112],"outperform":[57],"the":[58,78,97,113,117,126,137,150,160],"state-of-the-art":[59],"methods.":[60],"Our":[61],"estimator":[62,119],"uses":[63],"local":[64,83],"bandwidth":[65,98],"choices":[66],"k":[68,74],"-NN":[69],"distances":[70],"with":[71],"finite":[73],",":[75],"independent":[76,124,171],"sample":[79],"size.":[80],"Such":[81],"dependent":[86],"choice":[87],"ameliorates":[88],"boundary":[89],"bias":[90,115],"improves":[92],"performance":[93],"practice,":[95],"but":[96],"is":[99,120,123,169],"vanishing":[100],"at":[101],"fast":[103],"rate,":[104],"leading":[105],"non-vanishing":[108],"bias.":[109],"We":[110],"show":[111],"asymptotic":[114,161],"proposed":[118],"universal;":[121],"it":[122,130],"underlying":[127],"distribution.":[128],"Hence,":[129],"can":[131],"be":[132],"precomputed":[133],"subtracted":[135],"from":[136],"estimate.":[138],"As":[139],"byproduct,":[141],"obtain":[143],"unified":[145],"way":[146],"obtaining":[148],"kernel":[151],"NN":[153],"estimators.":[154],"The":[155],"corresponding":[156],"theoretical":[157],"contribution":[158],"relating":[159],"geometry":[162],"nearest":[164],"neighbors":[165],"order":[167],"statistics":[168],"mathematical":[172],"interest.":[173]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
