{"id":"https://openalex.org/W2025890108","doi":"https://doi.org/10.1109/lsp.2014.2378514","title":"Empirical Non-Parametric Estimation of the Fisher Information","display_name":"Empirical Non-Parametric Estimation of the Fisher Information","publication_year":2014,"publication_date":"2014-12-04","ids":{"openalex":"https://openalex.org/W2025890108","doi":"https://doi.org/10.1109/lsp.2014.2378514","mag":"2025890108"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2014.2378514","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2014.2378514","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1408.1182","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021646973","display_name":"Visar Berisha","orcid":"https://orcid.org/0000-0001-8804-8874"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Visar Berisha","raw_affiliation_strings":["Department of Speech and Hearing Science, Arizona State University, Tempe, AZ","School of Electrical Computer Energy Engineering (ECEE) Department of Speech and Hearing Science, Arizona State University, Tempe,"],"affiliations":[{"raw_affiliation_string":"Department of Speech and Hearing Science, Arizona State University, Tempe, AZ","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"School of Electrical Computer Energy Engineering (ECEE) Department of Speech and Hearing Science, Arizona State University, Tempe,","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077692655","display_name":"Alfred O. Hero","orcid":"https://orcid.org/0000-0002-2531-9670"},"institutions":[{"id":"https://openalex.org/I4210114445","display_name":"Michigan Medicine","ror":"https://ror.org/01zcpa714","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210114445"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alfred O. Hero","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science(EECS), Ann Arbor, MI","Department of Electrical Engineering and Computer Science(EECS), Ann Arbor,"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science(EECS), Ann Arbor, MI","institution_ids":["https://openalex.org/I4210114445"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science(EECS), Ann Arbor,","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5021646973"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":3.9912,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.94058787,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"22","issue":"7","first_page":"988","last_page":"992"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12261","display_name":"Statistical Mechanics and Entropy","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12261","display_name":"Statistical Mechanics and Entropy","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9962000250816345,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hessian-matrix","display_name":"Hessian matrix","score":0.794314980506897},{"id":"https://openalex.org/keywords/fisher-information","display_name":"Fisher information","score":0.791088342666626},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6476591229438782},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6329475045204163},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.6217876672744751},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5768292546272278},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.5682904124259949},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.5429915189743042},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.48689523339271545},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4793418347835541},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.4705137610435486},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4397459328174591},{"id":"https://openalex.org/keywords/curvature","display_name":"Curvature","score":0.43961861729621887},{"id":"https://openalex.org/keywords/empirical-distribution-function","display_name":"Empirical distribution function","score":0.4181373715400696}],"concepts":[{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.794314980506897},{"id":"https://openalex.org/C29406490","wikidata":"https://www.wikidata.org/wiki/Q1420659","display_name":"Fisher information","level":2,"score":0.791088342666626},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6476591229438782},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6329475045204163},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.6217876672744751},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5768292546272278},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5682904124259949},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.5429915189743042},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.48689523339271545},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4793418347835541},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.4705137610435486},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4397459328174591},{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.43961861729621887},{"id":"https://openalex.org/C98385598","wikidata":"https://www.wikidata.org/wiki/Q1339385","display_name":"Empirical distribution function","level":2,"score":0.4181373715400696},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2014.2378514","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2014.2378514","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1408.1182","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1408.1182","pdf_url":"https://arxiv.org/pdf/1408.1182","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1408.1182","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1408.1182","pdf_url":"https://arxiv.org/pdf/1408.1182","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2582260902","display_name":null,"funder_award_id":"CCF-1217880","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G649842886","display_name":null,"funder_award_id":"N000141410722","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G932903589","display_name":null,"funder_award_id":"W911NF-11-1-0391","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W195533127","https://openalex.org/W573190943","https://openalex.org/W1971672021","https://openalex.org/W1982105059","https://openalex.org/W1989000556","https://openalex.org/W2027238556","https://openalex.org/W2027390033","https://openalex.org/W2035764603","https://openalex.org/W2050275369","https://openalex.org/W2055309977","https://openalex.org/W2068276287","https://openalex.org/W2070696251","https://openalex.org/W2074269613","https://openalex.org/W2104220500","https://openalex.org/W2116566535","https://openalex.org/W2119582979","https://openalex.org/W2144578442","https://openalex.org/W2171151258","https://openalex.org/W2223385148","https://openalex.org/W3103871524","https://openalex.org/W4233131682","https://openalex.org/W4293404332","https://openalex.org/W6607976765","https://openalex.org/W6667880685"],"related_works":["https://openalex.org/W2611031068","https://openalex.org/W1704347466","https://openalex.org/W4283017538","https://openalex.org/W1996936972","https://openalex.org/W1545275724","https://openalex.org/W2802707792","https://openalex.org/W2569979269","https://openalex.org/W3212659400","https://openalex.org/W2153568439","https://openalex.org/W4225314943"],"abstract_inverted_index":{"The":[0,13,98],"Fisher":[1],"information":[2],"matrix":[3],"(FIM)":[4],"is":[5,60,100,143],"a":[6,24,79,109,117],"foundational":[7],"concept":[8],"in":[9,51],"statistical":[10],"signal":[11],"processing.":[12],"FIM":[14,33,84,135],"depends":[15],"on":[16,102],"the":[17,32,36,55,58,64,83,95,113,122,125,134,149],"probability":[18,37],"distribution,":[19],"assumed":[20],"to":[21,23,30,68],"belong":[22],"smooth":[25],"parametric":[26],"family.":[27],"Traditional":[28],"approaches":[29],"estimating":[31,35,82],"require":[34,92,139],"distribution":[38],"function":[39],"(PDF),":[40],"or":[41,48],"its":[42,46],"parameters,":[43],"along":[44],"with":[45],"gradient":[47],"Hessian.":[49],"However,":[50],"many":[52],"practical":[53],"situations":[54],"PDF":[56],"of":[57,81,94,105,112,121,133,151],"data":[59,88],"not":[61,91,138],"known":[62],"but":[63],"statistician":[65],"has":[66],"access":[67],"an":[69,106,130],"observation":[70],"sample":[71],"for":[72],"any":[73],"parameter":[74,114],"value.":[75],"Here":[76],"we":[77,128],"propose":[78],"method":[80,99],"directly":[85],"from":[86],"sampled":[87],"that":[89,136],"does":[90,137],"knowledge":[93],"underlying":[96],"PDF.":[97],"based":[101],"non-parametric":[103],"estimation":[104,141],"f-divergence":[107,123],"over":[108],"local":[110],"neighborhood":[111],"space":[115],"and":[116,124,142],"relation":[118],"between":[119],"curvature":[120],"FIM.":[126],"Thus":[127],"obtain":[129],"empirical":[131],"estimator":[132],"density":[140],"asymptotically":[144],"consistent.":[145],"We":[146],"empirically":[147],"evaluate":[148],"validity":[150],"our":[152],"approach":[153],"using":[154],"two":[155],"experiments.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":3}],"updated_date":"2026-04-12T07:58:50.170612","created_date":"2025-10-10T00:00:00"}