{"id":"https://openalex.org/W2902984567","doi":"https://doi.org/10.1109/icpr.2018.8546056","title":"Robust Projective Low-Rank and Sparse Representation by Robust Dictionary Learning","display_name":"Robust Projective Low-Rank and Sparse Representation by Robust Dictionary Learning","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902984567","doi":"https://doi.org/10.1109/icpr.2018.8546056","mag":"2902984567"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8546056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5079400113","display_name":"Jiahuan Ren","orcid":"https://orcid.org/0000-0002-5031-8952"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahuan Ren","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100423029","display_name":"Zhao Zhang","orcid":"https://orcid.org/0000-0002-5703-7969"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100359839","display_name":"Sheng Li","orcid":"https://orcid.org/0000-0003-1205-8632"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sheng Li","raw_affiliation_strings":["Adobc Research, Adobe Systems Inc, San Jose, California, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobc Research, Adobe Systems Inc, San Jose, California, United States","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019542310","display_name":"Guangcan Liu","orcid":"https://orcid.org/0000-0002-9428-4387"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangcan Liu","raw_affiliation_strings":["School of Information and Control, Nanjing University of Information Science and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Control, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100377147","display_name":"Meng Wang","orcid":"https://orcid.org/0000-0002-3094-7735"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Wang","raw_affiliation_strings":["School of Computer and Information Science, Hefei University of Technology, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Information Science, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100381753","display_name":"Shuicheng Yan","orcid":"https://orcid.org/0000-0001-8906-3777"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shuicheng Yan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, National University of Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":null,"first_page":"1851","last_page":"1856"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9950000047683716,"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/sparse-approximation","display_name":"Sparse approximation","score":0.7596515417098999},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.669954240322113},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5682873725891113},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5614292025566101},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.540937602519989},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5294475555419922},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5089752674102783},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48655882477760315},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4787684977054596},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.44249486923217773},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3783828318119049},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34764957427978516}],"concepts":[{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.7596515417098999},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.669954240322113},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5682873725891113},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5614292025566101},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.540937602519989},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5294475555419922},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5089752674102783},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48655882477760315},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4787684977054596},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.44249486923217773},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3783828318119049},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34764957427978516},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8546056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W282757658","https://openalex.org/W1736339626","https://openalex.org/W1987486886","https://openalex.org/W1992405901","https://openalex.org/W1995711748","https://openalex.org/W1997201895","https://openalex.org/W2021770241","https://openalex.org/W2068992789","https://openalex.org/W2069959554","https://openalex.org/W2070670538","https://openalex.org/W2076363162","https://openalex.org/W2100659887","https://openalex.org/W2112796928","https://openalex.org/W2135029798","https://openalex.org/W2140991832","https://openalex.org/W2145152441","https://openalex.org/W2145962650","https://openalex.org/W2148694408","https://openalex.org/W2160547390","https://openalex.org/W2166371785","https://openalex.org/W2313529869","https://openalex.org/W2748391982","https://openalex.org/W2754803257","https://openalex.org/W2962944036","https://openalex.org/W3143596294","https://openalex.org/W6680012447","https://openalex.org/W6684213969","https://openalex.org/W6744815318","https://openalex.org/W6776535907"],"related_works":["https://openalex.org/W2509955295","https://openalex.org/W1778286912","https://openalex.org/W1987225540","https://openalex.org/W2099321050","https://openalex.org/W2116933539","https://openalex.org/W4245251483","https://openalex.org/W2008821896","https://openalex.org/W1992008660","https://openalex.org/W2034957211","https://openalex.org/W1982147402"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"discuss":[4],"the":[5,32,54,61,71,78,90,96,101,113,121,131,146],"robust":[6,9,35,38,44,66,83],"factorization":[7,36,68,79,102],"based":[8,34,99],"dictionary":[10,45,104],"learning":[11,46],"problem":[12],"for":[13],"data":[14],"representation.":[15],"A":[16],"Robust":[17],"Projective":[18],"Low-Rank":[19],"and":[20,37,57,80,86,103,140],"Sparse":[21],"Representation":[22],"model":[23,30],"(R-PLSR)":[24],"is":[25],"technically":[26],"proposed.":[27],"Our":[28],"R-PLSR":[29,52,88,165],"integrates":[31],"L1-norm":[33,141],"low-rank":[39,56],"&":[40],"sparse":[41,58,67,91],"representation":[42,59,81,147],"by":[43,65],"into":[47],"a":[48],"unified":[49],"framework.":[50],"Specifically,":[51],"performs":[53],"joint":[55],"over":[60,171],"informative":[62],"low-dimensional":[63],"representations":[64,152],"so":[69,149],"that":[70,107,150,163],"results":[72,157],"are":[73,142],"more":[74],"accurate.":[75],"To":[76],"make":[77],"procedures":[82],"to":[84,126,135],"noise":[85],"outliers,":[87],"imposes":[89],"L2,":[92,108,122],"1-norm":[93,109,123],"jointly":[94,143],"on":[95,100,145,158],"reconstruction":[97,114,132],"errors":[98],"learning.":[105],"Note":[106],"can":[110,153,167],"also":[111],"minimize":[112],"error":[115,133],"as":[116,118],"much":[117],"possible,":[119],"since":[120],"theoretically":[124],"tends":[125],"force":[127],"many":[128],"rows":[129],"of":[130],"matrix":[134],"be":[136,154],"zeros.":[137],"The":[138],"Nuclear-norm":[139],"used":[144],"coefficients":[148],"salient":[151],"obtained.":[155],"Extensive":[156],"several":[159],"image":[160],"datasets":[161],"show":[162],"our":[164],"formulation":[166],"deliver":[168],"superior":[169],"performance":[170],"other":[172],"state-of-the-arts.":[173]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":6}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}