{"id":"https://openalex.org/W3126428072","doi":"https://doi.org/10.1109/tnnls.2023.3298011","title":"Robust Principal Component Analysis: A Median of Means Approach","display_name":"Robust Principal Component Analysis: A Median of Means Approach","publication_year":2023,"publication_date":"2023-08-07","ids":{"openalex":"https://openalex.org/W3126428072","doi":"https://doi.org/10.1109/tnnls.2023.3298011","mag":"3126428072","pmid":"https://pubmed.ncbi.nlm.nih.gov/37549093"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3298011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3298011","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5067874219","display_name":"Debolina Paul","orcid":"https://orcid.org/0000-0002-3981-9596"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Debolina Paul","raw_affiliation_strings":["Department of Statistics, Stanford University, Stanford, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3981-9596","affiliations":[{"raw_affiliation_string":"Department of Statistics, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076850079","display_name":"Saptarshi Chakraborty","orcid":"https://orcid.org/0000-0002-3668-637X"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saptarshi Chakraborty","raw_affiliation_strings":["Department of Statistics, University of California at Berkeley, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3668-637X","affiliations":[{"raw_affiliation_string":"Department of Statistics, University of California at Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000078546","display_name":"Swagatam Das","orcid":"https://orcid.org/0000-0001-6843-4508"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Swagatam Das","raw_affiliation_strings":["Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India","Institute for Advancing Intelligence (IAI), TCG CREST, Kolkata, India"],"raw_orcid":"https://orcid.org/0000-0001-6843-4508","affiliations":[{"raw_affiliation_string":"Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]},{"raw_affiliation_string":"Institute for Advancing Intelligence (IAI), TCG CREST, Kolkata, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5706,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.88558684,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"35","issue":"11","first_page":"16788","last_page":"16800"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9983999729156494,"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"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9965999722480774,"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":0.9919000267982483,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.8259538412094116},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7253430485725403},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6392310261726379},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5126394629478455},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5102689266204834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49670320749282837},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.46976491808891296},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.4663594961166382},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.459887832403183},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43952062726020813},{"id":"https://openalex.org/keywords/sparse-pca","display_name":"Sparse PCA","score":0.41869574785232544},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4186316728591919},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4012303948402405},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3472376763820648},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.32363057136535645}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.8259538412094116},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7253430485725403},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6392310261726379},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5126394629478455},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5102689266204834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49670320749282837},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.46976491808891296},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.4663594961166382},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.459887832403183},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43952062726020813},{"id":"https://openalex.org/C24252448","wikidata":"https://www.wikidata.org/wiki/Q7573786","display_name":"Sparse PCA","level":3,"score":0.41869574785232544},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4186316728591919},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4012303948402405},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3472376763820648},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.32363057136535645},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3298011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3298011","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37549093","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37549093","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W607505555","https://openalex.org/W1554944419","https://openalex.org/W1587559447","https://openalex.org/W1975900269","https://openalex.org/W2086943813","https://openalex.org/W2104052971","https://openalex.org/W2125027820","https://openalex.org/W2131628350","https://openalex.org/W2145962650","https://openalex.org/W2170586091","https://openalex.org/W2463344124","https://openalex.org/W2533545350","https://openalex.org/W2555690212","https://openalex.org/W2579923771","https://openalex.org/W2593894653","https://openalex.org/W2786088545","https://openalex.org/W2890107589","https://openalex.org/W2945560352","https://openalex.org/W2963290896","https://openalex.org/W2970905103","https://openalex.org/W3010140118","https://openalex.org/W3037561217","https://openalex.org/W3049487529","https://openalex.org/W3103790521","https://openalex.org/W3104099693","https://openalex.org/W3104624268","https://openalex.org/W3114559164","https://openalex.org/W3120740533"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W4391160746","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W1576424959","https://openalex.org/W3089231081"],"abstract_inverted_index":{"Principal":[0],"component":[1],"analysis":[2,150],"(PCA)":[3],"is":[4,16,30,96,151,178],"a":[5,82,154],"fundamental":[6],"tool":[7],"for":[8],"data":[9,186],"visualization,":[10],"denoising,":[11],"and":[12,25,37,158,184],"dimensionality":[13],"reduction.":[14],"It":[15],"widely":[17],"popular":[18],"in":[19,65,153,171],"statistics,":[20],"machine":[21],"learning,":[22],"computer":[23],"vision,":[24],"related":[26],"fields.":[27],"However,":[28],"PCA":[29,83],"well-known":[31],"to":[32,35,40,73],"fall":[33],"prey":[34],"outliers":[36],"often":[38],"fails":[39],"detect":[41],"the":[42,48,51,87,91,93,114,119,123,126,135,146,149,159,164,168,172],"true":[43],"underlying":[44,169],"low-dimensional":[45],"structure":[46],"within":[47],"dataset.":[49],"Following":[50],"Median":[52],"of":[53,118,125,167],"Means":[54],"(MoM)":[55],"philosophy,":[56],"recent":[57],"supervised":[58],"learning":[59],"methods":[60],"have":[61],"shown":[62],"great":[63],"success":[64],"dealing":[66],"with":[67],"outlying":[68,136],"observations":[69],"without":[70],"much":[71],"compromise":[72],"their":[74],"large":[75],"sample":[76],"theoretical":[77],"properties.":[78],"This":[79],"article":[80],"proposes":[81],"procedure":[84],"based":[85],"on":[86,134,145,163],"MoM":[88],"principle.":[89],"Called":[90],"MoMPCA,":[92],"proposed":[94],"method":[95],"not":[97,143],"only":[98,161],"computationally":[99],"appealing":[100],"but":[101],"also":[102,179],"achieves":[103],"optimal":[104],"convergence":[105],"rates":[106],"under":[107],"minimal":[108],"assumptions.":[109],"In":[110],"particular,":[111],"we":[112],"explore":[113],"nonasymptotic":[115],"error":[116],"bounds":[117],"obtained":[120],"solution":[121],"via":[122],"aid":[124],"Rademacher":[127],"complexities":[128],"while":[129],"granting":[130],"absolutely":[131],"no":[132],"assumption":[133],"observations.":[137],"The":[138,175],"derived":[139],"concentration":[140],"results":[141,160],"are":[142],"dependent":[144],"dimension":[147],"because":[148],"conducted":[152],"separable":[155],"Hilbert":[156],"space,":[157],"depend":[162],"fourth":[165],"moment":[166],"distribution":[170],"corresponding":[173],"norm.":[174],"proposal's":[176],"efficacy":[177],"thoroughly":[180],"showcased":[181],"through":[182],"simulations":[183],"real":[185],"applications.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}