{"id":"https://openalex.org/W3011615346","doi":"https://doi.org/10.1109/camsap45676.2019.9022635","title":"High Dimensional Robust Classification: A Random Matrix Analysis","display_name":"High Dimensional Robust Classification: A Random Matrix Analysis","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3011615346","doi":"https://doi.org/10.1109/camsap45676.2019.9022635","mag":"3011615346"},"language":"en","primary_location":{"id":"doi:10.1109/camsap45676.2019.9022635","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap45676.2019.9022635","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5021257434","display_name":"Romain Couillet","orcid":"https://orcid.org/0000-0001-5755-2090"},"institutions":[{"id":"https://openalex.org/I4210107720","display_name":"CentraleSup\u00e9lec","ror":"https://ror.org/019tcpt25","country_code":"FR","type":"facility","lineage":["https://openalex.org/I277688954","https://openalex.org/I4210107720"]},{"id":"https://openalex.org/I4210124956","display_name":"GIPSA-Lab","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Romain Couillet","raw_affiliation_strings":["GIPSA-lab, University Grenoble-Alpes CentraleSup\u00e9lec, University ParisSaclay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"GIPSA-lab, University Grenoble-Alpes CentraleSup\u00e9lec, University ParisSaclay","institution_ids":["https://openalex.org/I4210107720","https://openalex.org/I4210124956","https://openalex.org/I899635006"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021257434"],"corresponding_institution_ids":["https://openalex.org/I4210107720","https://openalex.org/I4210124956","https://openalex.org/I899635006"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"420","last_page":"424"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9991999864578247,"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":0.9991999864578247,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9973999857902527,"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":0.9955000281333923,"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/computer-science","display_name":"Computer science","score":0.5426318049430847},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4293104410171509},{"id":"https://openalex.org/keywords/matrix-algebra","display_name":"Matrix algebra","score":0.4104214012622833},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3889088034629822},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3323849141597748},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.13185641169548035},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1081351637840271},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.09324747323989868}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5426318049430847},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4293104410171509},{"id":"https://openalex.org/C2988995629","wikidata":"https://www.wikidata.org/wiki/Q2915729","display_name":"Matrix algebra","level":3,"score":0.4104214012622833},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3889088034629822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3323849141597748},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.13185641169548035},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1081351637840271},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.09324747323989868},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/camsap45676.2019.9022635","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap45676.2019.9022635","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04417377v1","is_oa":false,"landing_page_url":"https://hal.science/hal-04417377","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://camsap19.ig.umons.ac.be/","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"mag:3041231579","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002259753252771","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G115824985","display_name":"Random Matrix Theory for Large Dimensional Graphs","funder_award_id":"ANR-14-CE28-0006","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1971523416","https://openalex.org/W1974640819","https://openalex.org/W1979573625","https://openalex.org/W2008418230","https://openalex.org/W2039953809","https://openalex.org/W2046033161","https://openalex.org/W2112790040","https://openalex.org/W2132914434","https://openalex.org/W2143045817","https://openalex.org/W2165874743","https://openalex.org/W2577176882","https://openalex.org/W2963144092","https://openalex.org/W2963650649","https://openalex.org/W2963720057","https://openalex.org/W4255230573","https://openalex.org/W6684578312","https://openalex.org/W6732569707","https://openalex.org/W6745783979"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"This":[0,76],"article":[1],"proposes":[2],"a":[3,12],"random":[4],"matrix":[5,16],"analysis":[6],"of":[7,11,37,69,80],"the":[8,61,78],"spectral":[9],"properties":[10],"new":[13],"robust":[14,35,57],"kernel":[15,31],"model":[17],"adapted":[18],"to":[19],"elliptically":[20],"distributed":[21],"large":[22],"dimensional":[23],"data":[24],"mixtures.":[25],"It":[26],"is":[27],"shown":[28],"that":[29],"these":[30],"matrices,":[32],"based":[33],"on":[34],"estimators":[36,64],"scatter,":[38],"when":[39],"finely":[40],"tuned,":[41],"can":[42],"perform":[43],"asymptotic":[44,73],"non-trivial":[45],"(unsupervised)":[46],"classification":[47,74],"while":[48],"sample":[49],"covariance":[50],"matrices":[51],"are":[52],"ineffective.":[53],"Unlike":[54],"in":[55],"conventional":[56],"statistics":[58],"wisdom":[59],"though,":[60],"\u201cmaximally":[62],"robust\u201d":[63],"(such":[65],"as":[66],"Tyler's":[67],"estimator":[68],"scatter)":[70],"also":[71],"break":[72],"feasibility.":[75],"entails":[77],"existence":[79],"an":[81],"optimal":[82],"robustness-classification":[83],"trade-off":[84],"which":[85],"we":[86],"discuss.":[87]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}