{"id":"https://openalex.org/W2579893265","doi":"https://doi.org/10.1109/globalsip.2016.7905850","title":"Dictionary learning for sparse representation using weighted \u2113&lt;inf&gt;1&lt;/inf&gt;-norm","display_name":"Dictionary learning for sparse representation using weighted \u2113&lt;inf&gt;1&lt;/inf&gt;-norm","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2579893265","doi":"https://doi.org/10.1109/globalsip.2016.7905850","mag":"2579893265"},"language":"en","primary_location":{"id":"doi:10.1109/globalsip.2016.7905850","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2016.7905850","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","raw_type":"proceedings-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/A5023248590","display_name":"Haoli Zhao","orcid":"https://orcid.org/0000-0002-4004-509X"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Haoli Zhao","raw_affiliation_strings":["School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009582696","display_name":"Shuxue Ding","orcid":"https://orcid.org/0000-0002-4963-3883"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shuxue Ding","raw_affiliation_strings":["School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100340449","display_name":"Yujie Li","orcid":"https://orcid.org/0000-0002-5801-4937"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yujie Li","raw_affiliation_strings":["School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062429830","display_name":"Zhenni Li","orcid":"https://orcid.org/0000-0001-8098-0341"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhenni Li","raw_affiliation_strings":["School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100331094","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0002-9851-6376"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiang Li","raw_affiliation_strings":["School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030439103","display_name":"Benying Tan","orcid":"https://orcid.org/0000-0002-9121-8499"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Benying Tan","raw_affiliation_strings":["School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City, Fukushima, Japan","institution_ids":["https://openalex.org/I141591182"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5023248590"],"corresponding_institution_ids":["https://openalex.org/I141591182"],"apc_list":null,"apc_paid":null,"fwci":0.6079,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71002754,"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":"292","last_page":"296"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/norm","display_name":"Norm (philosophy)","score":0.7092123031616211},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.639583945274353},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5308986902236938},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.519464910030365},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.4642781615257263},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4453260004520416},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38222771883010864},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3440391421318054},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3307762145996094},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3289627730846405}],"concepts":[{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.7092123031616211},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.639583945274353},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5308986902236938},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.519464910030365},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.4642781615257263},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4453260004520416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38222771883010864},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3440391421318054},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3307762145996094},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3289627730846405},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globalsip.2016.7905850","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2016.7905850","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1914326009","https://openalex.org/W1999174140","https://openalex.org/W2018332268","https://openalex.org/W2056201402","https://openalex.org/W2078204800","https://openalex.org/W2108840817","https://openalex.org/W2113577207","https://openalex.org/W2115429828","https://openalex.org/W2118718620","https://openalex.org/W2142940228","https://openalex.org/W2153663612","https://openalex.org/W2160547390","https://openalex.org/W3122703110","https://openalex.org/W4235713725","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W2509955295","https://openalex.org/W1987225540","https://openalex.org/W2363993830","https://openalex.org/W1778286912","https://openalex.org/W2561456314","https://openalex.org/W2249096836","https://openalex.org/W2152958724","https://openalex.org/W2116933539","https://openalex.org/W1587263836","https://openalex.org/W1992008660"],"abstract_inverted_index":{"An":[0],"efficient":[1],"algorithm":[2,111],"for":[3],"overcomplete":[4],"dictionary":[5,128],"learning":[6,101],"with":[7],"l":[8,60,66],"<sub":[9,61,67],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[10,62,68],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">p</sub>":[11,69],"-norm":[12],"as":[13],"sparsity":[14],"constraint":[15],"to":[16,73,81,99,114,134],"achieve":[17],"sparse":[18,49],"representation":[19],"from":[20],"a":[21,54,74],"set":[22],"of":[23,34,127,131],"known":[24],"signals":[25],"is":[26,79,112],"presented":[27],"in":[28,45,117,124],"this":[29,85],"paper.":[30],"The":[31,65],"special":[32],"importance":[33],"the":[35,59,87,93,100,122],"\u00bfp-norm":[36],"(0":[37],"<;":[38,40],"\u03c1":[39],"1)":[41],"has":[42],"been":[43],"recognized":[44],"recent":[46],"studies":[47],"on":[48],"modeling,":[50],"which":[51,103],"can":[52],"lead":[53],"stronger":[55],"sparsity-promoting":[56],"solutions":[57],"than":[58],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[63],"-norm.":[64],"-norm,":[70],"however,":[71],"leads":[72],"nonconvex":[75],"optimization":[76],"problem":[77],"that":[78],"difficult":[80],"solve":[82],"efficiently.":[83],"In":[84],"paper,":[86],"hierarchically":[88],"alternating":[89],"update":[90],"strategy":[91],"and":[92,120,129,137],"weighted":[94],"\u00bfj-norm":[95],"method":[96],"are":[97],"introduced":[98],"procedure":[102],"find":[104],"local":[105],"optimal":[106],"at":[107],"each":[108],"iteration.":[109],"This":[110],"validated":[113],"be":[115],"effective":[116],"numerical":[118],"experiments":[119],"present":[121],"advantages":[123],"recovery":[125],"ratios":[126],"robustness":[130],"noise":[132],"compared":[133],"MOD,":[135],"K-SVD":[136],"FOCUSS-CNDL.":[138]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}