{"id":"https://openalex.org/W2766929895","doi":"https://doi.org/10.1109/tip.2017.2764622","title":"Marginalized Denoising Dictionary Learning With Locality Constraint","display_name":"Marginalized Denoising Dictionary Learning With Locality Constraint","publication_year":2017,"publication_date":"2017-10-20","ids":{"openalex":"https://openalex.org/W2766929895","doi":"https://doi.org/10.1109/tip.2017.2764622","mag":"2766929895","pmid":"https://pubmed.ncbi.nlm.nih.gov/29989998"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2017.2764622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2017.2764622","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100763639","display_name":"Shuyang Wang","orcid":"https://orcid.org/0000-0001-9471-0801"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shuyang Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083458247","display_name":"Zhengming Ding","orcid":"https://orcid.org/0000-0002-6994-5278"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengming Ding","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005819096","display_name":"Yun Fu","orcid":"https://orcid.org/0000-0002-5098-2853"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun Fu","raw_affiliation_strings":["Department of Electrical and Computer Engineering and the College of Computer and Information Science, Northeastern University, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and the College of Computer and Information Science, Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100763639"],"corresponding_institution_ids":["https://openalex.org/I12912129"],"apc_list":null,"apc_paid":null,"fwci":1.1833,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.87388974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"27","issue":"1","first_page":"500","last_page":"510"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9980999827384949,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9980999827384949,"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":0.9939000010490417,"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/discriminative-model","display_name":"Discriminative model","score":0.7203536629676819},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.7189149856567383},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6756943464279175},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6583267450332642},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6507374048233032},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5883838534355164},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.515933096408844},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.5153452754020691},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.505082905292511},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49959897994995117},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.4283338189125061},{"id":"https://openalex.org/keywords/local-consistency","display_name":"Local consistency","score":0.41250288486480713},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.37099042534828186},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35796457529067993},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20187699794769287},{"id":"https://openalex.org/keywords/constraint-satisfaction","display_name":"Constraint satisfaction","score":0.11748397350311279},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.07750102877616882}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7203536629676819},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.7189149856567383},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6756943464279175},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6583267450332642},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6507374048233032},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5883838534355164},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.515933096408844},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.5153452754020691},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.505082905292511},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49959897994995117},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4283338189125061},{"id":"https://openalex.org/C137105694","wikidata":"https://www.wikidata.org/wiki/Q3407510","display_name":"Local consistency","level":4,"score":0.41250288486480713},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.37099042534828186},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35796457529067993},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20187699794769287},{"id":"https://openalex.org/C44616089","wikidata":"https://www.wikidata.org/wiki/Q30158686","display_name":"Constraint satisfaction","level":3,"score":0.11748397350311279},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.07750102877616882},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2017.2764622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2017.2764622","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:29989998","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29989998","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3571051887","display_name":null,"funder_award_id":"W911NF-17-1-0367","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G6838734070","display_name":null,"funder_award_id":"1651902","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8569619938","display_name":null,"funder_award_id":"N00014-14-1-0484","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W79405465","https://openalex.org/W191001584","https://openalex.org/W283029246","https://openalex.org/W1471821242","https://openalex.org/W1591385104","https://openalex.org/W1669104078","https://openalex.org/W1905307128","https://openalex.org/W1937777952","https://openalex.org/W1963932623","https://openalex.org/W1975815261","https://openalex.org/W1993055204","https://openalex.org/W1997201895","https://openalex.org/W2000355138","https://openalex.org/W2002574940","https://openalex.org/W2006793117","https://openalex.org/W2007588387","https://openalex.org/W2025768430","https://openalex.org/W2027922120","https://openalex.org/W2028930140","https://openalex.org/W2035128422","https://openalex.org/W2035746673","https://openalex.org/W2038964396","https://openalex.org/W2072128103","https://openalex.org/W2084716923","https://openalex.org/W2088843485","https://openalex.org/W2089397669","https://openalex.org/W2090101874","https://openalex.org/W2096873754","https://openalex.org/W2097018403","https://openalex.org/W2097486709","https://openalex.org/W2103560185","https://openalex.org/W2105132921","https://openalex.org/W2108665656","https://openalex.org/W2112796928","https://openalex.org/W2118622562","https://openalex.org/W2121647436","https://openalex.org/W2125874614","https://openalex.org/W2134563198","https://openalex.org/W2145094598","https://openalex.org/W2145962650","https://openalex.org/W2152061189","https://openalex.org/W2157785665","https://openalex.org/W2166371785","https://openalex.org/W2219037758","https://openalex.org/W2294193936","https://openalex.org/W2604308885","https://openalex.org/W2949821452","https://openalex.org/W2994340921","https://openalex.org/W2997574889","https://openalex.org/W4231109964","https://openalex.org/W6603183647","https://openalex.org/W6607783561","https://openalex.org/W6637225622","https://openalex.org/W6639835855","https://openalex.org/W6651042577","https://openalex.org/W6659319144","https://openalex.org/W6672484794","https://openalex.org/W6674642818","https://openalex.org/W6676231525","https://openalex.org/W6679809621","https://openalex.org/W6681096077","https://openalex.org/W6684213969","https://openalex.org/W6696958782","https://openalex.org/W6736314251"],"related_works":["https://openalex.org/W2509955295","https://openalex.org/W2572092625","https://openalex.org/W2771430809","https://openalex.org/W1987225540","https://openalex.org/W2363993830","https://openalex.org/W2008821896","https://openalex.org/W2561456314","https://openalex.org/W1992008660","https://openalex.org/W1587263836","https://openalex.org/W1778286912"],"abstract_inverted_index":{"Learning":[0],"good":[1],"representation":[2],"for":[3,27],"images":[4],"is":[5,23],"always":[6],"a":[7,24,98,110,140],"hot":[8],"topic":[9],"in":[10,88,136],"machine":[11],"learning":[12,22,42,101,113],"and":[13,56,66,128,143,162,172],"pattern":[14],"recognition":[15],"fields.":[16],"Among":[17],"the":[18,70,74,81,105,149,170],"numerous":[19],"algorithms,":[20],"dictionary":[21,41,112,118],"well-known":[25],"strategy":[26],"effective":[28],"feature":[29,91,100,145],"extraction.":[30],"Recently,":[31],"more":[32,141],"discriminative":[33,40],"sub-dictionaries":[34],"have":[35,168],"been":[36],"built":[37],"by":[38,103,178],"Fisher":[39],"with":[43,180],"specific":[44],"class":[45],"labels.":[46],"Different":[47],"types":[48],"of":[49,64,78,132,174],"constraints,":[50],"such":[51],"as":[52,73],"sparsity,":[53],"low":[54],"rankness,":[55],"locality,":[57],"are":[58],"also":[59],"exploited":[60],"to":[61,138],"make":[62],"use":[63],"global":[65],"local":[67],"information.":[68],"On":[69],"other":[71],"hand,":[72],"basic":[75],"building":[76],"block":[77],"deep":[79],"structure,":[80],"auto-encoder":[82,108],"has":[83],"demonstrated":[84,169],"its":[85],"promising":[86],"performance":[87],"extracting":[89],"new":[90],"representation.":[92],"To":[93],"this":[94],"end,":[95],"we":[96,121,155],"develop":[97],"unified":[99],"framework":[102],"incorporating":[104],"marginalized":[106,116],"denoising":[107,117],"into":[109],"locality-constrained":[111],"scheme,":[114],"named":[115],"learning.":[119,153],"Overall,":[120],"deploy":[122],"low-rank":[123],"constraint":[124,130],"on":[125,134,159],"each":[126],"sub-dictionary":[127,152],"locality":[129],"instead":[131],"sparsity":[133],"coefficients,":[135],"order":[137],"learn":[139],"concise":[142],"pure":[144],"spaces":[146],"meanwhile":[147],"inheriting":[148],"discrimination":[150],"from":[151],"Finally,":[154],"evaluate":[156],"our":[157,175],"algorithm":[158,177],"several":[160,181],"face":[161],"object":[163],"data":[164],"sets.":[165],"Experimental":[166],"results":[167],"effectiveness":[171],"efficiency":[173],"proposed":[176],"comparing":[179],"state-of-the-art":[182],"methods.":[183]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}