{"id":"https://openalex.org/W1122559001","doi":"https://doi.org/10.3233/ida-140706","title":"Generalizing the Mahalanobis distance via density kernels","display_name":"Generalizing the Mahalanobis distance via density kernels","publication_year":2014,"publication_date":"2014-11-01","ids":{"openalex":"https://openalex.org/W1122559001","doi":"https://doi.org/10.3233/ida-140706","mag":"1122559001"},"language":"en","primary_location":{"id":"doi:10.3233/ida-140706","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-140706","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis: An International Journal","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":"https://openalex.org/A5027371351","display_name":"Gabriel Martos","orcid":"https://orcid.org/0000-0002-7677-2088"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Gabriel Martos","raw_affiliation_strings":["Department of Statistics, University Carlos III, Madrid, Spain","Department of Statistics, University Carlos III, Madrid, Spain#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University Carlos III, Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]},{"raw_affiliation_string":"Department of Statistics, University Carlos III, Madrid, Spain#TAB#","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042880273","display_name":"Alberto Mu\u00f1oz","orcid":"https://orcid.org/0000-0001-8982-0678"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Alberto Mu\u00f1oz","raw_affiliation_strings":["Department of Statistics, University Carlos III, Madrid, Spain","Department of Statistics, University Carlos III, Madrid, Spain#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University Carlos III, Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]},{"raw_affiliation_string":"Department of Statistics, University Carlos III, Madrid, Spain#TAB#","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110790091","display_name":"Javier Gonz\u00e1lez","orcid":null},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Javier Gonz\u00e1lez","raw_affiliation_strings":["Sheffield Institute for Translational Neuroscience, The University of Sheffield, Sheffield, UK","Sheffield Institute for Translational Neuroscience, The University of Sheffield, Sheffield, UK#TAB#"],"affiliations":[{"raw_affiliation_string":"Sheffield Institute for Translational Neuroscience, The University of Sheffield, Sheffield, UK","institution_ids":["https://openalex.org/I91136226"]},{"raw_affiliation_string":"Sheffield Institute for Translational Neuroscience, The University of Sheffield, Sheffield, UK#TAB#","institution_ids":["https://openalex.org/I91136226"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027371351"],"corresponding_institution_ids":["https://openalex.org/I50357001"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.0282067,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"18","issue":"6_suppl","first_page":"S19","last_page":"S31"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9970999956130981,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9970999956130981,"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/T10057","display_name":"Face and Expression Recognition","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9872000217437744,"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/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.9226409196853638},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4784657657146454},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3803597092628479},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3681854009628296},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3648200035095215},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32703351974487305}],"concepts":[{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.9226409196853638},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4784657657146454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3803597092628479},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3681854009628296},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3648200035095215},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32703351974487305}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-140706","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-140706","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis: An International Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1540596182","https://openalex.org/W1560879229","https://openalex.org/W1580791986","https://openalex.org/W1964410470","https://openalex.org/W1996118086","https://openalex.org/W2015887370","https://openalex.org/W2038410888","https://openalex.org/W2104433707","https://openalex.org/W2116805437","https://openalex.org/W2132984323","https://openalex.org/W2147152072","https://openalex.org/W2151996692","https://openalex.org/W2169487163","https://openalex.org/W2263859115","https://openalex.org/W2492055736"],"related_works":["https://openalex.org/W4382795578","https://openalex.org/W1431147547","https://openalex.org/W2355463328","https://openalex.org/W2402648945","https://openalex.org/W2055761197","https://openalex.org/W2053213469","https://openalex.org/W2771741613","https://openalex.org/W2057608111","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"The":[0],"Mahalanobis":[1],"distance":[2,6,33,98],"(MD)":[3],"is":[4],"a":[5,21,35,54,104],"widely":[7],"used":[8],"in":[9],"Statistics,":[10],"Machine":[11],"Learning":[12],"and":[13,38,77,99,108],"Pattern":[14],"Recognition.":[15],"When":[16],"the":[17,24,27,32,39,47,60,65,75,87,92,96],"data":[18,36,67,82,110],"come":[19],"from":[20],"Gaussian":[22,88],"distribution,":[23],"MD":[25,48,76],"uses":[26],"covariance":[28],"matrix":[29],"to":[30,86],"evaluate":[31],"between":[34],"point":[37],"distribution":[40],"mean.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45],"generalize":[46,74],"for":[49],"general":[50],"unimodal":[51],"distributions,":[52],"introducing":[53],"particular":[55],"class":[56],"of":[57,95,106],"Mercer":[58],"kernel,":[59,62],"density":[61],"based":[63],"on":[64,103],"underlying":[66],"density.":[68],"Density":[69],"kernels":[70],"induce":[71],"distances":[72],"that":[73,78],"are":[79],"useful":[80],"when":[81],"do":[83],"not":[84],"fit":[85],"distribution.":[89],"We":[90],"study":[91],"theoretical":[93],"properties":[94],"proposed":[97],"show":[100],"its":[101],"performance":[102],"variety":[105],"artificial":[107],"real":[109],"analysis":[111],"problems.":[112]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
