{"id":"https://openalex.org/W3013047998","doi":"https://doi.org/10.1109/ieeeconf44664.2019.9048980","title":"Combinatorial Search for the Lp-Norm Principal Component of a Matrix","display_name":"Combinatorial Search for the Lp-Norm Principal Component of a Matrix","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3013047998","doi":"https://doi.org/10.1109/ieeeconf44664.2019.9048980","mag":"3013047998"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf44664.2019.9048980","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf44664.2019.9048980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 53rd Asilomar Conference on Signals, Systems, and Computers","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/A5016447762","display_name":"Dimitris G. Chachlakis","orcid":"https://orcid.org/0000-0002-6464-0723"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dimitris G. Chachlakis","raw_affiliation_strings":["Rochester Institute of Technology,Dept. of Electrical and Microelectronic Engineering,Rochester,NY,USA","Dept. of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology,Dept. of Electrical and Microelectronic Engineering,Rochester,NY,USA","institution_ids":["https://openalex.org/I155173764"]},{"raw_affiliation_string":"Dept. of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010876698","display_name":"Panos P. Markopoulos","orcid":"https://orcid.org/0000-0001-9686-779X"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Panos P. Markopoulos","raw_affiliation_strings":["Rochester Institute of Technology,Dept. of Electrical and Microelectronic Engineering,Rochester,NY,USA","Dept. of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology,Dept. of Electrical and Microelectronic Engineering,Rochester,NY,USA","institution_ids":["https://openalex.org/I155173764"]},{"raw_affiliation_string":"Dept. of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155173764"],"apc_list":null,"apc_paid":null,"fwci":0.3823,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.5721748,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1611","last_page":"1615"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987999796867371,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.991599977016449,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.7907387018203735},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.7468397617340088},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.6617149710655212},{"id":"https://openalex.org/keywords/sparse-pca","display_name":"Sparse PCA","score":0.6494752764701843},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6107536554336548},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5862191319465637},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5358380675315857},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5292291641235352},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4791940152645111},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.46483680605888367},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4380192756652832},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4293251633644104},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.41165173053741455},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.39752334356307983},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.38028618693351746},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.26862412691116333},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1657690703868866},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08384943008422852}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7907387018203735},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.7468397617340088},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.6617149710655212},{"id":"https://openalex.org/C24252448","wikidata":"https://www.wikidata.org/wiki/Q7573786","display_name":"Sparse PCA","level":3,"score":0.6494752764701843},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6107536554336548},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5862191319465637},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5358380675315857},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5292291641235352},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4791940152645111},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.46483680605888367},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4380192756652832},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4293251633644104},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.41165173053741455},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.39752334356307983},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38028618693351746},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.26862412691116333},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1657690703868866},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08384943008422852},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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":1,"locations":[{"id":"doi:10.1109/ieeeconf44664.2019.9048980","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf44664.2019.9048980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 53rd Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W147992333","https://openalex.org/W1509829222","https://openalex.org/W1518039036","https://openalex.org/W1539726260","https://openalex.org/W1740511963","https://openalex.org/W1970655212","https://openalex.org/W2014374971","https://openalex.org/W2065281378","https://openalex.org/W2097581696","https://openalex.org/W2098004870","https://openalex.org/W2101117936","https://openalex.org/W2113642685","https://openalex.org/W2120580172","https://openalex.org/W2145962650","https://openalex.org/W2167421362","https://openalex.org/W2266946488","https://openalex.org/W2277192409","https://openalex.org/W2293883257","https://openalex.org/W2331052961","https://openalex.org/W2529352582","https://openalex.org/W2611695496","https://openalex.org/W2625898145","https://openalex.org/W2742341851","https://openalex.org/W2765321384","https://openalex.org/W2798909945","https://openalex.org/W2804273032","https://openalex.org/W2891665990","https://openalex.org/W2894994225","https://openalex.org/W2903545545","https://openalex.org/W2904047372","https://openalex.org/W2919186794","https://openalex.org/W2945990941","https://openalex.org/W2963484948","https://openalex.org/W2995423737","https://openalex.org/W3003567092","https://openalex.org/W3003874369","https://openalex.org/W3105049931","https://openalex.org/W4298082496","https://openalex.org/W6605914596","https://openalex.org/W6637603442","https://openalex.org/W6649031020","https://openalex.org/W6675479683","https://openalex.org/W6684559340","https://openalex.org/W6737658887","https://openalex.org/W6885107840","https://openalex.org/W6993175652"],"related_works":["https://openalex.org/W2906988372","https://openalex.org/W2776058083","https://openalex.org/W2990436289","https://openalex.org/W2732461152","https://openalex.org/W2006410278","https://openalex.org/W2309638141","https://openalex.org/W2574182783","https://openalex.org/W2732959879","https://openalex.org/W4291805341","https://openalex.org/W2929137829"],"abstract_inverted_index":{"We":[0],"study":[1],"Lp-norm":[2],"Principal-Component":[3],"Analysis":[4],"(Lp-PCA)":[5],"of":[6,45,97],"a":[7],"matrix.":[8],"For":[9,25,42],"p":[10,26,70,99],"=":[11,27],"2":[12],"(standard":[13],"PCA),":[14],"the":[15,30,47,60,64,83,94],"problem":[16,31],"can":[17,74],"be":[18,75],"solved":[19,34,76],"with":[20,38],"standard":[21],"Singular-Value":[22],"Decomposition":[23],"(SVD).":[24],"1":[28],"(L1-PCA),":[29],"was":[32],"recently":[33],"exactly":[35,77],"and":[36,81],"approximately":[37],"efficient":[39],"iterative":[40],"algorithms.":[41],"general":[43],"values":[44],"p,":[46],"exact":[48,85],"solution":[49],"to":[50,53],"Lp-PCA":[51,73],"remains":[52],"date":[54],"unknown.":[55],"In":[56],"this":[57],"work,":[58],"for":[59,69],"first":[61,84],"time":[62],"in":[63],"literature,":[65],"we":[66],"prove":[67],"that,":[68],"\u2264":[71,100],"1,":[72,101],"through":[78],"combinatorial":[79],"optimization":[80],"present":[82],"solver.":[86],"Our":[87],"experimental":[88],"studies":[89],"on":[90],"medical":[91],"data":[92],"demonstrate":[93],"significant":[95],"robustness":[96],"Lp-PCA,":[98],"against":[102],"outliers.":[103]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}