{"id":"https://openalex.org/W3195692608","doi":"https://doi.org/10.1109/ssp49050.2021.9513843","title":"Robust Probabilistic Simplex Component Analysis","display_name":"Robust Probabilistic Simplex Component Analysis","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3195692608","doi":"https://doi.org/10.1109/ssp49050.2021.9513843","mag":"3195692608"},"language":"en","primary_location":{"id":"doi:10.1109/ssp49050.2021.9513843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp49050.2021.9513843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-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/A5101883509","display_name":"Yuening Li","orcid":"https://orcid.org/0000-0001-9324-4781"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuening Li","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong SAR of China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong SAR of China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016986549","display_name":"Wing\u2010Kin Ma","orcid":"https://orcid.org/0000-0001-7314-3537"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wing-Kin Ma","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong SAR of China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong SAR of China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050186120","display_name":"Nicholas D. Sidiropoulos","orcid":"https://orcid.org/0000-0002-3385-7911"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas D. Sidiropoulos","raw_affiliation_strings":["University of Virginia, Charlottesville, Virginia, USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, Virginia, USA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101883509"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":0.2493,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58326284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"53","issue":null,"first_page":"456","last_page":"460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9624000191688538,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/outlier","display_name":"Outlier","score":0.8251996636390686},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7952491044998169},{"id":"https://openalex.org/keywords/simplex","display_name":"Simplex","score":0.7140989303588867},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6708450317382812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.640039324760437},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6379002332687378},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.549781084060669},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5456103682518005},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5162003636360168},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4991569519042969},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4913720190525055},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.483039915561676},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.4556844234466553},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.42225730419158936},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.389058381319046},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32951200008392334},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24393624067306519}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8251996636390686},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7952491044998169},{"id":"https://openalex.org/C62438384","wikidata":"https://www.wikidata.org/wiki/Q331350","display_name":"Simplex","level":2,"score":0.7140989303588867},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6708450317382812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.640039324760437},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6379002332687378},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.549781084060669},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5456103682518005},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5162003636360168},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4991569519042969},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4913720190525055},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.483039915561676},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.4556844234466553},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.42225730419158936},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.389058381319046},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32951200008392334},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24393624067306519},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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":1,"locations":[{"id":"doi:10.1109/ssp49050.2021.9513843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp49050.2021.9513843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W584423923","https://openalex.org/W1854811422","https://openalex.org/W1966872876","https://openalex.org/W1976615758","https://openalex.org/W2044758663","https://openalex.org/W2046793177","https://openalex.org/W2049633694","https://openalex.org/W2063790512","https://openalex.org/W2081555128","https://openalex.org/W2123649031","https://openalex.org/W2125027820","https://openalex.org/W2125118959","https://openalex.org/W2129062845","https://openalex.org/W2134328014","https://openalex.org/W2137969290","https://openalex.org/W2157321686","https://openalex.org/W2163886442","https://openalex.org/W2169924573","https://openalex.org/W2185164352","https://openalex.org/W2326945647","https://openalex.org/W2507533531","https://openalex.org/W2513096609","https://openalex.org/W2763081248","https://openalex.org/W2791154158","https://openalex.org/W2964085075","https://openalex.org/W2964257934","https://openalex.org/W3100202987","https://openalex.org/W3114089334","https://openalex.org/W3138879901","https://openalex.org/W4205699356","https://openalex.org/W4253803149","https://openalex.org/W6639041367","https://openalex.org/W6791667463"],"related_works":["https://openalex.org/W2063021680","https://openalex.org/W2357922472","https://openalex.org/W2384278689","https://openalex.org/W2386777115","https://openalex.org/W2563365141","https://openalex.org/W2924917467","https://openalex.org/W2073891040","https://openalex.org/W1510133244","https://openalex.org/W1968042686","https://openalex.org/W2009059033"],"abstract_inverted_index":{"Simplex":[0],"component":[1],"analysis":[2],"(SCA)":[3],"is":[4,50,74],"an":[5],"important":[6],"problem":[7],"that":[8,100],"finds":[9],"diverse":[10],"applications":[11],"from":[12,25],"hyperspectral":[13],"imaging":[14],"to":[15,52,76],"topic":[16],"mining":[17],"and":[18,41,56,81,89,96,108],"community":[19],"detection.":[20,91],"This":[21],"contribution":[22],"revisits":[23],"SCA":[24],"a":[26,39,47,66],"probabilistic":[27],"point":[28],"of":[29,34,59],"view,":[30],"with":[31,36,94],"the":[32,54,57,60,78,82,101],"aim":[33],"dealing":[35],"outliers":[37],"in":[38],"disciplined":[40],"effective":[42],"way.":[43],"Towards":[44],"this":[45],"end,":[46],"mixture":[48,61],"distribution":[49],"used":[51,75],"model":[53,62,87],"data,":[55],"parameters":[58],"are":[63],"sought":[64],"via":[65],"maximum":[67],"likelihood":[68],"formulation.":[69],"A":[70],"variational":[71],"inference":[72],"approximation":[73],"tackle":[77],"resulting":[79],"problem,":[80],"solution":[83],"enables":[84],"simultaneous":[85],"nominal":[86],"estimation":[88],"outlier":[90,109],"Careful":[92],"simulations":[93],"synthetic":[95],"semi-real":[97],"data":[98],"reveal":[99],"proposed":[102],"approach":[103],"offers":[104],"significantly":[105],"improved":[106],"robustness":[107],"detection":[110],"capabilities.":[111]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}