{"id":"https://openalex.org/W4402469571","doi":"https://doi.org/10.1080/10618600.2024.2402280","title":"Efficient Convex PCA with Applications to Wasserstein GPCA and Ranked Data","display_name":"Efficient Convex PCA with Applications to Wasserstein GPCA and Ranked Data","publication_year":2024,"publication_date":"2024-09-12","ids":{"openalex":"https://openalex.org/W4402469571","doi":"https://doi.org/10.1080/10618600.2024.2402280"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2024.2402280","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2402280","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102233107","display_name":"Steven Campbell","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Steven Campbell","raw_affiliation_strings":["Department of Statistics, Columbia University"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053260623","display_name":"Ting\u2010Kam Leonard Wong","orcid":"https://orcid.org/0000-0001-5254-7305"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ting-Kam Leonard Wong","raw_affiliation_strings":["Department of Statistical Sciences, University of Toronto"],"affiliations":[{"raw_affiliation_string":"Department of Statistical Sciences, University of Toronto","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102233107"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":1.3897,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.82349166,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"34","issue":"2","first_page":"540","last_page":"551"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9717000126838684,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9717000126838684,"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/T11413","display_name":"Risk and Portfolio Optimization","score":0.9573000073432922,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9247000217437744,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5539565682411194},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.5375745892524719},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39655691385269165},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3808016777038574},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.35894227027893066},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33459413051605225},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.32036495208740234},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.09398317337036133}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5539565682411194},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.5375745892524719},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39655691385269165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3808016777038574},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.35894227027893066},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33459413051605225},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.32036495208740234},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09398317337036133}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/10618600.2024.2402280","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2402280","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},{"id":"pmh:doi:10.6084/m9.figshare.27011401","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"pmh:doi:10.6084/m9.figshare.27011401","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322015","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1953394243","https://openalex.org/W1968333723","https://openalex.org/W1998824578","https://openalex.org/W2009366157","https://openalex.org/W2019691043","https://openalex.org/W2024257794","https://openalex.org/W2029763864","https://openalex.org/W2086591901","https://openalex.org/W2100011707","https://openalex.org/W2127674094","https://openalex.org/W2174145043","https://openalex.org/W2587050086","https://openalex.org/W2795320988","https://openalex.org/W3035649090","https://openalex.org/W3124524932","https://openalex.org/W3125234093","https://openalex.org/W3136862634","https://openalex.org/W3154256386","https://openalex.org/W3209271283","https://openalex.org/W4205465859","https://openalex.org/W4206471589","https://openalex.org/W4233762729","https://openalex.org/W4250589301","https://openalex.org/W4255103909","https://openalex.org/W4301668100","https://openalex.org/W4400611568","https://openalex.org/W4401846005","https://openalex.org/W4409315341"],"related_works":["https://openalex.org/W1922851888","https://openalex.org/W2406961220","https://openalex.org/W3188962172","https://openalex.org/W2772917594","https://openalex.org/W2046260256","https://openalex.org/W4306742369","https://openalex.org/W4303457083","https://openalex.org/W4232468313","https://openalex.org/W2131146434","https://openalex.org/W2951359407"],"abstract_inverted_index":{"Convex":[0],"PCA,":[1],"which":[2,139],"was":[3],"introduced":[4],"by":[5,12,130],"<i>Bigot":[6],"et":[7],"al.</i>":[8],"modifies":[9],"Euclidean":[10],"PCA":[11,97],"restricting":[13],"the":[14,17,42,53,79,83,99,133],"data":[15,40,51],"and":[16,48,76,104,132],"principal":[18],"components":[19],"to":[20],"lie":[21],"in":[22,35,41,58,82,144],"a":[23,28,90,109],"given":[24],"convex":[25,96,100],"subset":[26],"of":[27,45,78,93,112,126,138,141],"Hilbert":[29],"space.":[30],"This":[31],"setting":[32],"arises":[33],"naturally":[34],"many":[36],"applications,":[37,123],"including":[38,70],"distributional":[39],"Wasserstein":[43,113],"space":[44],"an":[46],"interval,":[47],"ranked":[49,129],"compositional":[50],"under":[52],"Aitchison":[54],"geometry.":[55],"Our":[56],"contribution":[57],"this":[59,107,151],"article":[60,152],"is":[61,102],"3-fold.":[62],"First,":[63],"we":[64,88,116],"present":[65],"several":[66],"new":[67],"theoretical":[68],"results":[69,119],"consistency":[71],"as":[72,74],"well":[73],"continuity":[75],"differentiability":[77],"objective":[80],"function":[81],"finite":[84,94],"dimensional":[85,95],"case.":[86],"Second,":[87],"develop":[89],"numerical":[91],"implementation":[92],"when":[98],"set":[101],"polyhedral,":[103],"show":[105],"that":[106],"provides":[108],"natural":[110],"approximation":[111],"GPCA.":[114],"Third,":[115],"illustrate":[117],"our":[118],"with":[120],"two":[121],"financial":[122],"namely":[124],"distributions":[125],"stock":[127],"returns":[128],"size":[131],"capital":[134],"distribution":[135],"curve,":[136],"both":[137],"are":[140,153],"independent":[142],"interest":[143],"stochastic":[145],"portfolio":[146],"theory.":[147],"Supplementary":[148],"materials":[149],"for":[150],"available":[154],"online.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
