{"id":"https://openalex.org/W3209241975","doi":"https://doi.org/10.3390/a14110322","title":"Robust Bilinear Probabilistic Principal Component Analysis","display_name":"Robust Bilinear Probabilistic Principal Component Analysis","publication_year":2021,"publication_date":"2021-11-01","ids":{"openalex":"https://openalex.org/W3209241975","doi":"https://doi.org/10.3390/a14110322","mag":"3209241975"},"language":"en","primary_location":{"id":"doi:10.3390/a14110322","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a14110322","pdf_url":"https://www.mdpi.com/1999-4893/14/11/322/pdf?version=1635931180","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/14/11/322/pdf?version=1635931180","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079534401","display_name":"Yaohang Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I61057504","display_name":"Fujian Agriculture and Forestry University","ror":"https://ror.org/04kx2sy84","country_code":"CN","type":"education","lineage":["https://openalex.org/I61057504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaohang Lu","raw_affiliation_strings":["College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China","institution_ids":["https://openalex.org/I61057504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085791276","display_name":"Zhongming Teng","orcid":"https://orcid.org/0000-0003-1533-1534"},"institutions":[{"id":"https://openalex.org/I61057504","display_name":"Fujian Agriculture and Forestry University","ror":"https://ror.org/04kx2sy84","country_code":"CN","type":"education","lineage":["https://openalex.org/I61057504"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhongming Teng","raw_affiliation_strings":["College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China","institution_ids":["https://openalex.org/I61057504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5085791276"],"corresponding_institution_ids":["https://openalex.org/I61057504"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14530577,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"11","first_page":"322","last_page":"322"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9986000061035156,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9926000237464905,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9898999929428101,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6640617847442627},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.63660728931427},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6288444399833679},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5985289812088013},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5847971439361572},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5584189295768738},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5290992259979248},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.49910759925842285},{"id":"https://openalex.org/keywords/bilinear-interpolation","display_name":"Bilinear interpolation","score":0.4786432981491089},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.45642751455307007},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4373050332069397},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3822571933269501},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3270658254623413},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12096589803695679},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.07666891813278198}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6640617847442627},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.63660728931427},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6288444399833679},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5985289812088013},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5847971439361572},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5584189295768738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5290992259979248},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.49910759925842285},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.4786432981491089},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.45642751455307007},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4373050332069397},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3822571933269501},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3270658254623413},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12096589803695679},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.07666891813278198},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/a14110322","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a14110322","pdf_url":"https://www.mdpi.com/1999-4893/14/11/322/pdf?version=1635931180","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a226d30d8ec741a4a23804bedfa1a54b","is_oa":true,"landing_page_url":"https://doaj.org/article/a226d30d8ec741a4a23804bedfa1a54b","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 14, Iss 11, p 322 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1999-4893/14/11/322/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/a14110322","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms; Volume 14; Issue 11; Pages: 322","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/a14110322","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a14110322","pdf_url":"https://www.mdpi.com/1999-4893/14/11/322/pdf?version=1635931180","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/12","score":0.5400000214576721,"display_name":"Responsible consumption and production"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3209241975.pdf","grobid_xml":"https://content.openalex.org/works/W3209241975.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1541521713","https://openalex.org/W1664859298","https://openalex.org/W1807984730","https://openalex.org/W1973247608","https://openalex.org/W2018326237","https://openalex.org/W2024476015","https://openalex.org/W2029202499","https://openalex.org/W2038371718","https://openalex.org/W2044822299","https://openalex.org/W2076201826","https://openalex.org/W2094034700","https://openalex.org/W2102544846","https://openalex.org/W2125027820","https://openalex.org/W2126111600","https://openalex.org/W2151673022","https://openalex.org/W2604744783","https://openalex.org/W2611015177","https://openalex.org/W2963971081","https://openalex.org/W3107476107","https://openalex.org/W3148198191","https://openalex.org/W4211128380","https://openalex.org/W4242722506","https://openalex.org/W4303105520","https://openalex.org/W6808577644"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241","https://openalex.org/W2354420595"],"abstract_inverted_index":{"Principal":[0],"component":[1],"analysis":[2],"(PCA)":[3],"is":[4,131],"one":[5],"of":[6,66,76,115,154],"the":[7,22,35,43,63,74,113,121,135,152],"most":[8],"popular":[9],"tools":[10],"in":[11,85,103,158],"multivariate":[12],"exploratory":[13],"data":[14,60,93,146],"analysis.":[15],"Its":[16],"probabilistic":[17,28],"version":[18],"(PPCA)":[19],"based":[20],"on":[21,140],"maximum":[23],"likelihood":[24],"procedure":[25],"provides":[26],"a":[27,108],"manner":[29],"to":[30,54,97,133,150],"implement":[31],"dimension":[32],"reduction.":[33],"Recently,":[34],"bilinear":[36],"PPCA":[37],"(BPPCA)":[38],"model,":[39],"which":[40,88],"assumes":[41],"that":[42],"noise":[44,122],"terms":[45],"follow":[46],"matrix":[47,64,116],"variate":[48,117],"Gaussian":[49,79],"distributions,":[50],"has":[51],"been":[52],"introduced":[53],"directly":[55],"deal":[56],"with":[57],"two-dimensional":[58],"(2-D)":[59],"for":[61,101,120],"preserving":[62],"structure":[65],"2-D":[67],"data,":[68],"such":[69],"as":[70],"images,":[71],"and":[72,143,162],"avoiding":[73],"curse":[75],"dimensionality.":[77],"However,":[78],"distributions":[80,119],"are":[81,148],"not":[82],"always":[83],"available":[84,145],"real-life":[86],"applications":[87],"may":[89],"contain":[90],"outliers":[91],"within":[92],"sets.":[94],"In":[95],"order":[96],"make":[98],"BPPCA":[99,110],"robust":[100,109],"outliers,":[102],"this":[104],"paper,":[105],"we":[106],"propose":[107],"model":[111,136,157],"under":[112],"assumption":[114],"t":[118],"terms.":[123],"The":[124],"alternating":[125],"expectation":[126],"conditional":[127],"maximization":[128],"(AECM)":[129],"algorithm":[130],"used":[132],"estimate":[134],"parameters.":[137],"Numerical":[138],"examples":[139],"several":[141],"synthetic":[142],"publicly":[144],"sets":[147],"presented":[149],"demonstrate":[151],"superiority":[153],"our":[155],"proposed":[156],"feature":[159],"extraction,":[160],"classification":[161],"outlier":[163],"detection.":[164]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2021-11-08T00:00:00"}
