{"id":"https://openalex.org/W2963118864","doi":"https://doi.org/10.1007/s12532-019-00163-5","title":"A hybrid quasi-Newton projected-gradient method with application to Lasso and basis-pursuit denoising","display_name":"A hybrid quasi-Newton projected-gradient method with application to Lasso and basis-pursuit denoising","publication_year":2019,"publication_date":"2019-06-04","ids":{"openalex":"https://openalex.org/W2963118864","doi":"https://doi.org/10.1007/s12532-019-00163-5","mag":"2963118864"},"language":"en","primary_location":{"id":"doi:10.1007/s12532-019-00163-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12532-019-00163-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12532-019-00163-5.pdf","source":{"id":"https://openalex.org/S173077093","display_name":"Mathematical Programming Computation","issn_l":"1867-2949","issn":["1867-2949","1867-2957"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mathematical Programming Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s12532-019-00163-5.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091640094","display_name":"E. van den Berg","orcid":"https://orcid.org/0000-0002-0991-3397"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ewout van den Berg","raw_affiliation_strings":["IBM T.J. Watson Research Center, 1101 Kitchawan Rd, Yorktown Heights, NY 10598, USA","IBM T.J. Watson Research Center, 1101 Kitchawan Rd, Yorktown Heights, NY, 10598, USA"],"affiliations":[{"raw_affiliation_string":"IBM T.J. Watson Research Center, 1101 Kitchawan Rd, Yorktown Heights, NY 10598, USA","institution_ids":["https://openalex.org/I1341412227"]},{"raw_affiliation_string":"IBM T.J. Watson Research Center, 1101 Kitchawan Rd, Yorktown Heights, NY, 10598, USA","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5091640094"],"corresponding_institution_ids":["https://openalex.org/I1341412227"],"apc_list":{"value":2390,"currency":"EUR","value_usd":3090},"apc_paid":{"value":2390,"currency":"EUR","value_usd":3090},"fwci":0.5823,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.65386147,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"12","issue":"1","first_page":"1","last_page":"38"},"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/T11205","display_name":"Numerical methods in inverse problems","score":0.9983999729156494,"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"}},{"id":"https://openalex.org/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/basis-pursuit","display_name":"Basis pursuit","score":0.7352489829063416},{"id":"https://openalex.org/keywords/broyden\u2013fletcher\u2013goldfarb\u2013shanno-algorithm","display_name":"Broyden\u2013Fletcher\u2013Goldfarb\u2013Shanno algorithm","score":0.6220107674598694},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5666654706001282},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.5574355125427246},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.5305101275444031},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5237845778465271},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5059565901756287},{"id":"https://openalex.org/keywords/iterated-function","display_name":"Iterated function","score":0.49120277166366577},{"id":"https://openalex.org/keywords/conjugate-gradient-method","display_name":"Conjugate gradient method","score":0.4635984003543854},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4243733286857605},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.42225125432014465},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4153946042060852},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35551416873931885},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.20242053270339966},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17968371510505676},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.1301022469997406}],"concepts":[{"id":"https://openalex.org/C99217422","wikidata":"https://www.wikidata.org/wiki/Q4867576","display_name":"Basis pursuit","level":4,"score":0.7352489829063416},{"id":"https://openalex.org/C132721684","wikidata":"https://www.wikidata.org/wiki/Q2877013","display_name":"Broyden\u2013Fletcher\u2013Goldfarb\u2013Shanno algorithm","level":3,"score":0.6220107674598694},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5666654706001282},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.5574355125427246},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.5305101275444031},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5237845778465271},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5059565901756287},{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.49120277166366577},{"id":"https://openalex.org/C81184566","wikidata":"https://www.wikidata.org/wiki/Q1191895","display_name":"Conjugate gradient method","level":2,"score":0.4635984003543854},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4243733286857605},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.42225125432014465},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4153946042060852},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35551416873931885},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.20242053270339966},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17968371510505676},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.1301022469997406},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"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/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s12532-019-00163-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12532-019-00163-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12532-019-00163-5.pdf","source":{"id":"https://openalex.org/S173077093","display_name":"Mathematical Programming Computation","issn_l":"1867-2949","issn":["1867-2949","1867-2957"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mathematical Programming Computation","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s12532-019-00163-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12532-019-00163-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12532-019-00163-5.pdf","source":{"id":"https://openalex.org/S173077093","display_name":"Mathematical Programming Computation","issn_l":"1867-2949","issn":["1867-2949","1867-2957"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mathematical Programming Computation","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2088627233","display_name":null,"funder_award_id":"DMS 0906812","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5627406188","display_name":"High dimensional data: new phenomena and theory in modeling and approximation","funder_award_id":"0906812","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963118864.pdf","grobid_xml":"https://content.openalex.org/works/W2963118864.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1953936588","https://openalex.org/W1973734200","https://openalex.org/W1978259121","https://openalex.org/W1986931325","https://openalex.org/W1999997491","https://openalex.org/W2006262045","https://openalex.org/W2013439434","https://openalex.org/W2032693829","https://openalex.org/W2051434435","https://openalex.org/W2076605490","https://openalex.org/W2080233464","https://openalex.org/W2083042020","https://openalex.org/W2093575660","https://openalex.org/W2103955025","https://openalex.org/W2129131372","https://openalex.org/W2132347401","https://openalex.org/W2135046866","https://openalex.org/W2145096794","https://openalex.org/W2256400397","https://openalex.org/W2296616510","https://openalex.org/W2607928667","https://openalex.org/W2798766386","https://openalex.org/W2963173886","https://openalex.org/W4230517232","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W2207919472","https://openalex.org/W2906115589","https://openalex.org/W3210179682","https://openalex.org/W2078029965","https://openalex.org/W2097581546","https://openalex.org/W2098528027","https://openalex.org/W2625259661","https://openalex.org/W2544771389","https://openalex.org/W1984722404","https://openalex.org/W2136780394"],"abstract_inverted_index":{"We":[0,37],"propose":[1],"a":[2,12],"new":[3],"algorithm":[4,20,42,49,79],"for":[5],"the":[6,22,32,41,48,52,57,62,102],"optimization":[7],"of":[8,40],"convex":[9],"functions":[10],"over":[11],"polyhedral":[13],"set":[14],"in":[15],"R":[16],"n":[17],".":[18],"The":[19,78],"extends":[21],"spectral":[23],"projected-gradient":[24],"method":[25],"with":[26],"limited-memory":[27],"BFGS":[28],"iterates":[29],"restricted":[30,100],"to":[31,50,84,92,101],"present":[33],"face":[34],"whenever":[35],"possible.":[36],"prove":[38],"convergence":[39],"under":[43],"suitable":[44],"conditions":[45],"and":[46,55,70,87],"apply":[47],"solve":[51,93],"Lasso":[53],"problem,":[54],"consequently,":[56],"basis-pursuit":[58],"denoise":[59],"problem":[60],"through":[61],"root-finding":[63],"framework":[64],"proposed":[65],"by":[66],"van":[67],"den":[68],"Berg":[69],"Friedlander":[71],"(SIAM":[72],"J":[73],"Sci":[74],"Comput":[75],"31(2):890-912,":[76],"2008).":[77],"is":[80],"especially":[81],"well":[82,97],"suited":[83],"simple":[85],"domains":[86],"could":[88],"also":[89],"be":[90],"used":[91],"bound-constrained":[94],"problems":[95,99],"as":[96,98],"simplex.":[103]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
