{"id":"https://openalex.org/W3022380717","doi":"https://doi.org/10.1109/jstsp.2007.910971","title":"An Interior-Point Method for Large-Scale -Regularized Least Squares","display_name":"An Interior-Point Method for Large-Scale -Regularized Least Squares","publication_year":2007,"publication_date":"2007-12-01","ids":{"openalex":"https://openalex.org/W3022380717","doi":"https://doi.org/10.1109/jstsp.2007.910971","mag":"3022380717"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2007.910971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2007.910971","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},"type":"article","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/A5026356137","display_name":"Seung-Jean Kim","orcid":null},"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":true,"raw_author_name":"Seung-Jean Kim","raw_affiliation_strings":["Information Systems Lab, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Information Systems Lab, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109249218","display_name":"Kwangmoo Koh","orcid":null},"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":"K. Koh","raw_affiliation_strings":["Information Systems Lab, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Information Systems Lab, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082297273","display_name":"Michael Lustig","orcid":"https://orcid.org/0000-0002-4794-221X"},"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":"M. Lustig","raw_affiliation_strings":["Information Systems Lab, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Information Systems Lab, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011176205","display_name":"Stephen Boyd","orcid":"https://orcid.org/0000-0001-8353-6000"},"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":"Stephen Boyd","raw_affiliation_strings":["Information Systems Lab, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Information Systems Lab, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043201307","display_name":"Dimitry Gorinevsky","orcid":"https://orcid.org/0000-0002-9595-0863"},"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":"Dimitry Gorinevsky","raw_affiliation_strings":["Information Systems Lab, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Information Systems Lab, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5026356137"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":93.8349,"has_fulltext":false,"cited_by_count":2082,"citation_normalized_percentile":{"value":0.99990608,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"1","issue":"4","first_page":"606","last_page":"617"},"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11205","display_name":"Numerical methods in inverse problems","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"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/compressed-sensing","display_name":"Compressed sensing","score":0.7328906655311584},{"id":"https://openalex.org/keywords/interior-point-method","display_name":"Interior point method","score":0.7327902317047119},{"id":"https://openalex.org/keywords/basis-pursuit","display_name":"Basis pursuit","score":0.732543408870697},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.6223430037498474},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5959585905075073},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5876501202583313},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5820022821426392},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.5246745944023132},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.5058369636535645},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5026934146881104},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4829396605491638},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.46486884355545044},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.4564100205898285},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4043659567832947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21914568543434143},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09027859568595886}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7328906655311584},{"id":"https://openalex.org/C155253501","wikidata":"https://www.wikidata.org/wiki/Q461992","display_name":"Interior point method","level":2,"score":0.7327902317047119},{"id":"https://openalex.org/C99217422","wikidata":"https://www.wikidata.org/wiki/Q4867576","display_name":"Basis pursuit","level":4,"score":0.732543408870697},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.6223430037498474},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5959585905075073},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5876501202583313},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5820022821426392},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.5246745944023132},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.5058369636535645},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5026934146881104},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4829396605491638},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.46486884355545044},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.4564100205898285},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4043659567832947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21914568543434143},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09027859568595886},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstsp.2007.910971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2007.910971","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":76,"referenced_works":["https://openalex.org/W182881619","https://openalex.org/W1480376833","https://openalex.org/W1506342804","https://openalex.org/W1509805685","https://openalex.org/W1518039036","https://openalex.org/W1523109900","https://openalex.org/W1568288633","https://openalex.org/W1760551737","https://openalex.org/W1965755064","https://openalex.org/W1968694834","https://openalex.org/W1977252496","https://openalex.org/W1993273815","https://openalex.org/W2010824638","https://openalex.org/W2011181254","https://openalex.org/W2015263936","https://openalex.org/W2019787708","https://openalex.org/W2020925091","https://openalex.org/W2027197817","https://openalex.org/W2047316561","https://openalex.org/W2056636001","https://openalex.org/W2062102668","https://openalex.org/W2063978378","https://openalex.org/W2078204800","https://openalex.org/W2097323375","https://openalex.org/W2097897435","https://openalex.org/W2098012923","https://openalex.org/W2101932199","https://openalex.org/W2103559027","https://openalex.org/W2105235982","https://openalex.org/W2109449402","https://openalex.org/W2115706991","https://openalex.org/W2118064110","https://openalex.org/W2119862467","https://openalex.org/W2122825543","https://openalex.org/W2127300249","https://openalex.org/W2133958955","https://openalex.org/W2135046866","https://openalex.org/W2135850876","https://openalex.org/W2138019504","https://openalex.org/W2143476164","https://openalex.org/W2144011735","https://openalex.org/W2145096794","https://openalex.org/W2146482778","https://openalex.org/W2147656689","https://openalex.org/W2149206122","https://openalex.org/W2150722533","https://openalex.org/W2150940164","https://openalex.org/W2157434051","https://openalex.org/W2163989778","https://openalex.org/W2164452299","https://openalex.org/W2168204766","https://openalex.org/W2170967306","https://openalex.org/W2171585467","https://openalex.org/W2296319761","https://openalex.org/W2296616510","https://openalex.org/W2595697910","https://openalex.org/W2795929191","https://openalex.org/W2796501268","https://openalex.org/W2997644599","https://openalex.org/W3017068026","https://openalex.org/W3023659858","https://openalex.org/W3029645440","https://openalex.org/W3098834468","https://openalex.org/W3105702746","https://openalex.org/W3131899091","https://openalex.org/W3147239081","https://openalex.org/W4211092921","https://openalex.org/W4239881334","https://openalex.org/W4241131157","https://openalex.org/W4250589301","https://openalex.org/W4250955649","https://openalex.org/W4293775970","https://openalex.org/W4301491118","https://openalex.org/W4302155765","https://openalex.org/W6679665003","https://openalex.org/W6682241100"],"related_works":["https://openalex.org/W2388133936","https://openalex.org/W2067878805","https://openalex.org/W2436826437","https://openalex.org/W2086419783","https://openalex.org/W2523302315","https://openalex.org/W2059024629","https://openalex.org/W1983115982","https://openalex.org/W2340242818","https://openalex.org/W2907652444","https://openalex.org/W2103001330"],"abstract_inverted_index":{"Recently,":[0],"a":[1,79,109,115,121,151],"lot":[2],"of":[3,118],"attention":[4],"has":[5],"been":[6],"paid":[7],"to":[8,95],"regularization":[9],"based":[10],"methods":[11,61],"for":[12,68,83,143],"sparse":[13,106,133],"signal":[14,31,134],"reconstruction":[15],"(e.g.,":[16,26],"basis":[17],"pursuit":[18],"denoising":[19],"and":[20,23,34,55,70,112],"compressed":[21],"sensing)":[22],"feature":[24],"selection":[25],"the":[27,90,97],"Lasso":[28],"algorithm)":[29],"in":[30,114,132],"processing,":[32],"statistics,":[33],"related":[35],"fields.":[36],"These":[37],"problems":[38],"can":[39,48,103,124],"be":[40,49],"cast":[41],"as":[42,51,63],"-regularized":[43,86],"least-squares":[44],"programs":[45],"(LSPs),":[46],"which":[47],"reformulated":[50],"convex":[52],"quadratic":[53],"programs,":[54],"then":[56],"solved":[57],"by":[58,139],"several":[59],"standard":[60],"such":[62],"interior-point":[64,81,101],"methods,":[65],"at":[66],"least":[67],"small":[69],"medium":[71],"size":[72],"problems.":[73],"In":[74],"this":[75],"paper,":[76],"we":[77],"describe":[78],"specialized":[80],"method":[82,102,147],"solving":[84],"large-scale":[85],"LSPs":[87],"that":[88,130],"uses":[89],"preconditioned":[91],"conjugate":[92],"gradients":[93],"algorithm":[94],"compute":[96],"search":[98],"direction.":[99],"The":[100,146],"solve":[104,126],"large":[105,127],"problems,":[107,129],"with":[108,136],"million":[110],"variables":[111],"observations,":[113],"few":[116],"tens":[117],"minutes":[119],"on":[120,150],"PC.":[122],"It":[123],"efficiently":[125],"dense":[128],"arise":[131],"recovery":[135],"orthogonal":[137],"transforms,":[138],"exploiting":[140],"fast":[141],"algorithms":[142],"these":[144],"transforms.":[145],"is":[148],"illustrated":[149],"magnetic":[152],"resonance":[153],"imaging":[154],"data":[155],"set.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":53},{"year":2024,"cited_by_count":74},{"year":2023,"cited_by_count":77},{"year":2022,"cited_by_count":84},{"year":2021,"cited_by_count":140},{"year":2020,"cited_by_count":100},{"year":2019,"cited_by_count":107},{"year":2018,"cited_by_count":124},{"year":2017,"cited_by_count":140},{"year":2016,"cited_by_count":157},{"year":2015,"cited_by_count":165},{"year":2014,"cited_by_count":164},{"year":2013,"cited_by_count":182},{"year":2012,"cited_by_count":150}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}