{"id":"https://openalex.org/W4293699880","doi":"https://doi.org/10.1109/access.2022.3198597","title":"Spectrum Pursuit With Residual Descent for Column Subset Selection Problem: Theoretical Guarantees and Applications in Deep Learning","display_name":"Spectrum Pursuit With Residual Descent for Column Subset Selection Problem: Theoretical Guarantees and Applications in Deep Learning","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4293699880","doi":"https://doi.org/10.1109/access.2022.3198597"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3198597","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3198597","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09855488.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09855488.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049755417","display_name":"Saeed Vahidian","orcid":"https://orcid.org/0000-0002-1258-0343"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saeed Vahidian","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California at San Diego, San Diego, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1258-0343","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California at San Diego, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038914007","display_name":"Mohsen Joneidi","orcid":"https://orcid.org/0000-0001-5955-4049"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohsen Joneidi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031027300","display_name":"Ashkan Esmaeili","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ashkan Esmaeili","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069121108","display_name":"Siavash Khodadadeh","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siavash Khodadadeh","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010971864","display_name":"Sharareh Zehtabian","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sharareh Zehtabian","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061781904","display_name":"Bill Lin","orcid":"https://orcid.org/0000-0003-0965-7247"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bill Lin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California at San Diego, San Diego, CA, USA"],"raw_orcid":"https://orcid.org/0000-0003-0965-7247","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California at San Diego, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2804,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.42688636,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"10","issue":null,"first_page":"88164","last_page":"88177"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9991999864578247,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9984999895095825,"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/rank","display_name":"Rank (graph theory)","score":0.6971725225448608},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.6031991243362427},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5926007628440857},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4795474708080292},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.46018677949905396},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4571208655834198},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.4543936550617218},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4373202919960022},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.42052987217903137},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36914384365081787},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19043302536010742}],"concepts":[{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6971725225448608},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.6031991243362427},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5926007628440857},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4795474708080292},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.46018677949905396},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4571208655834198},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.4543936550617218},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4373202919960022},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.42052987217903137},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36914384365081787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19043302536010742},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3198597","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3198597","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09855488.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d694a664994940d2a94cd26d68076b31","is_oa":true,"landing_page_url":"https://doaj.org/article/d694a664994940d2a94cd26d68076b31","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 88164-88177 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3198597","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3198597","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09855488.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5614476323","display_name":"Collaborative Research:RI:AF:Medium:Exchanging Knowledge Beyond Data Between Human and Machine Learner","funder_award_id":"1956339","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4293699880.pdf","grobid_xml":"https://content.openalex.org/works/W4293699880.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W61851215","https://openalex.org/W1925032196","https://openalex.org/W1966872876","https://openalex.org/W1968200975","https://openalex.org/W1973117123","https://openalex.org/W1982716240","https://openalex.org/W1982811641","https://openalex.org/W1993962865","https://openalex.org/W1998269045","https://openalex.org/W2044610104","https://openalex.org/W2089135543","https://openalex.org/W2089757006","https://openalex.org/W2101043704","https://openalex.org/W2119233169","https://openalex.org/W2123904976","https://openalex.org/W2147276092","https://openalex.org/W2153959628","https://openalex.org/W2166500461","https://openalex.org/W2274655698","https://openalex.org/W2302255633","https://openalex.org/W2405479119","https://openalex.org/W2499720122","https://openalex.org/W2547648546","https://openalex.org/W2612467436","https://openalex.org/W2798593490","https://openalex.org/W2888819926","https://openalex.org/W2904509905","https://openalex.org/W2912990735","https://openalex.org/W2950958145","https://openalex.org/W2963149653","https://openalex.org/W2963877232","https://openalex.org/W2972401521","https://openalex.org/W2992671401","https://openalex.org/W3015854362","https://openalex.org/W3037079313","https://openalex.org/W3088364660","https://openalex.org/W3135387830","https://openalex.org/W3176453655","https://openalex.org/W4247692611","https://openalex.org/W4289236186","https://openalex.org/W6677246231","https://openalex.org/W6682725716","https://openalex.org/W6686261702","https://openalex.org/W6694787318","https://openalex.org/W6713057566","https://openalex.org/W6713485569","https://openalex.org/W6737232052","https://openalex.org/W6740418354","https://openalex.org/W6748798142","https://openalex.org/W6764346752","https://openalex.org/W6767373300","https://openalex.org/W6767630037","https://openalex.org/W6767849677","https://openalex.org/W7045342168"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W4306886878","https://openalex.org/W2973759123","https://openalex.org/W3014540454"],"abstract_inverted_index":{"We":[0,82],"propose":[1,58],"a":[2,12,52,73,84,246,265,290],"novel":[3],"technique":[4],"for":[5,88,112,227,283],"dataset":[6,36],"summarization":[7],"by":[8,126,141],"selecting":[9],"representatives":[10],"from":[11],"large,":[13],"unsupervised":[14],"dataset.":[15],"The":[16,107],"approach":[17],"is":[18,146,189,199,208,221],"based":[19],"on":[20,264],"the":[21,27,43,46,68,79,89,93,103,127,155,171,178,192,217,228,261,285],"concept":[22],"of":[23,30,49,76,95,136,157,177,239],"self-rank,":[24],"defined":[25],"as":[26,201,279],"minimum":[28],"number":[29,156,194],"samples":[31,37,71,101],"needed":[32],"to":[33,42,102,191,224,259],"express":[34],"all":[35],"with":[38,292],"an":[39,59,164],"accuracy":[40],"proportional":[41,190],"rank-Kapproximation.":[44],"As":[45],"exact":[47],"computation":[48],"self-rank":[50,65],"requires":[51],"computationally":[53],"expensive":[54],"combinatorial":[55],"search,":[56,144],"we":[57,162,268],"efficient":[60],"algorithm":[61,233,263],"that":[62,167,270],"jointly":[63],"estimates":[64],"and":[66,149,174,207,251,295],"selects":[67],"most":[69],"informative":[70],"in":[72,118,131,210,244,254,275],"linear":[74,235],"order":[75],"complexity":[77,236],"w.r.t":[78],"data":[80],"size.":[81],"derive":[83],"new":[85],"upper":[86],"bound":[87,128,188],"approximation":[90,115],"ratio":[91,94],"(AR),":[92],"obtained":[96,140],"projection":[97],"error":[98],"using":[99],"selected":[100,158],"best":[104,108],"rank-Kapproximation":[105],"error.":[106],"previously":[109],"known":[110],"AR":[111,166,198,220],"self-representative":[113],"low-rank":[114],"was":[116,123],"presented":[117],"ICML":[119],"2017":[120],"[1],":[121],"which":[122,145,204,242],"further":[124],"improved":[125],"√1":[129],"+Kreported":[130],"NeurIPS":[132],"2019":[133],"[2].":[134],"Both":[135],"these":[137,150],"bounds":[138,151],"are":[139],"brute":[142],"force":[143],"not":[147,223],"practical,":[148],"depend":[152],"solely":[153],"onK,":[154],"samples.":[159],"In":[160,184,216,257],"contrast,":[161],"describe":[163],"adaptive":[165],"takes":[168],"into":[169],"consideration":[170],"spectral":[172,213],"properties":[173],"spikiness":[175],"measure":[176],"original":[179,240],"dataset,":[180,241,267],"A":[181],"ϵ":[182],"RN×M.":[183],"particular,":[185],"our":[186],"performance":[187],"condition":[193],"κ(A).":[195],"Our":[196,231],"derived":[197],"expressed":[200],"1+(κ(A)2-":[202],"1)/(N-K),":[203],"approaches":[205],"1":[206],"optimal":[209],"two":[211],"extreme":[212],"distribution":[214],"instances.":[215],"worst":[218],"case,":[219],"shown":[222],"exceed":[225],"1.25":[226],"proposed":[229,232,262],"method.":[230],"enjoys":[234],"w.r.t.":[237],"size":[238],"results":[243],"filling":[245],"historical":[247],"gap":[248],"between":[249],"practical":[250],"theoretical":[252],"methods":[253],"finding":[255],"representatives.":[256],"addition":[258],"evaluating":[260],"synthetic":[266],"show":[269],"it":[271],"can":[272],"be":[273],"utilized":[274],"real-world":[276],"applications":[277],"such":[278],"graph":[280],"node":[281],"sampling":[282],"optimizing":[284],"shortest":[286],"path":[287],"criterion,":[288],"learning":[289],"classifier":[291],"representative":[293],"data,":[294],"open-set":[296],"identification.":[297]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}