{"id":"https://openalex.org/W3093889873","doi":"https://doi.org/10.1109/access.2020.3033484","title":"Robust Dictionary Learning and Sparse Coding With Riemannian Geometry Preserving Method in Symmetric Matrices Inner Product Space","display_name":"Robust Dictionary Learning and Sparse Coding With Riemannian Geometry Preserving Method in Symmetric Matrices Inner Product Space","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3093889873","doi":"https://doi.org/10.1109/access.2020.3033484","mag":"3093889873"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3033484","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3033484","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09238028.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09238028.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101418802","display_name":"Yang Zhang","orcid":"https://orcid.org/0000-0002-8109-2095"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Zhang","raw_affiliation_strings":["Communication and Information Security Laboratory, Shenzhen Graduate School, Peking University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-8109-2095","affiliations":[{"raw_affiliation_string":"Communication and Information Security Laboratory, Shenzhen Graduate School, Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056706680","display_name":"Yuesheng Zhu","orcid":"https://orcid.org/0000-0003-2524-6800"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuesheng Zhu","raw_affiliation_strings":["Communication and Information Security Laboratory, Shenzhen Graduate School, Peking University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2524-6800","affiliations":[{"raw_affiliation_string":"Communication and Information Security Laboratory, Shenzhen Graduate School, Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.175,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.47034494,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"8","issue":null,"first_page":"197068","last_page":"197085"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987999796867371,"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":0.9987999796867371,"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/T10057","display_name":"Face and Expression Recognition","score":0.9970999956130981,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9936000108718872,"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/robustness","display_name":"Robustness (evolution)","score":0.5670806169509888},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5503565073013306},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.5463933348655701},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.54246586561203},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5341659188270569},{"id":"https://openalex.org/keywords/reproducing-kernel-hilbert-space","display_name":"Reproducing kernel Hilbert space","score":0.5263168811798096},{"id":"https://openalex.org/keywords/inner-product-space","display_name":"Inner product space","score":0.5147514343261719},{"id":"https://openalex.org/keywords/riemannian-geometry","display_name":"Riemannian geometry","score":0.445893794298172},{"id":"https://openalex.org/keywords/hilbert-space","display_name":"Hilbert space","score":0.4359123110771179},{"id":"https://openalex.org/keywords/symmetric-matrix","display_name":"Symmetric matrix","score":0.43299829959869385},{"id":"https://openalex.org/keywords/riemannian-manifold","display_name":"Riemannian manifold","score":0.42559826374053955},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36756378412246704},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35278230905532837},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.12199586629867554},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.12139838933944702}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5670806169509888},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5503565073013306},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.5463933348655701},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.54246586561203},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5341659188270569},{"id":"https://openalex.org/C80884492","wikidata":"https://www.wikidata.org/wiki/Q3345678","display_name":"Reproducing kernel Hilbert space","level":3,"score":0.5263168811798096},{"id":"https://openalex.org/C91855343","wikidata":"https://www.wikidata.org/wiki/Q214159","display_name":"Inner product space","level":2,"score":0.5147514343261719},{"id":"https://openalex.org/C181104567","wikidata":"https://www.wikidata.org/wiki/Q761383","display_name":"Riemannian geometry","level":2,"score":0.445893794298172},{"id":"https://openalex.org/C62799726","wikidata":"https://www.wikidata.org/wiki/Q190056","display_name":"Hilbert space","level":2,"score":0.4359123110771179},{"id":"https://openalex.org/C54848796","wikidata":"https://www.wikidata.org/wiki/Q339011","display_name":"Symmetric matrix","level":3,"score":0.43299829959869385},{"id":"https://openalex.org/C2779593128","wikidata":"https://www.wikidata.org/wiki/Q632814","display_name":"Riemannian manifold","level":2,"score":0.42559826374053955},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36756378412246704},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35278230905532837},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.12199586629867554},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.12139838933944702},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","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},{"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3033484","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3033484","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09238028.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fbd01f0a2d8a475a84d72941e7992e79","is_oa":true,"landing_page_url":"https://doaj.org/article/fbd01f0a2d8a475a84d72941e7992e79","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 197068-197085 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3033484","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3033484","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09238028.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6600000262260437,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2433373925","display_name":null,"funder_award_id":"U1613215","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327511","display_name":"Development and Reform Commission of Shenzhen Municipality","ror":"https://ror.org/03jmg4515"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3093889873.pdf","grobid_xml":"https://content.openalex.org/works/W3093889873.grobid-xml"},"referenced_works_count":67,"referenced_works":["https://openalex.org/W8105021","https://openalex.org/W78159342","https://openalex.org/W157436748","https://openalex.org/W1479760883","https://openalex.org/W1508406818","https://openalex.org/W1510073064","https://openalex.org/W1515954165","https://openalex.org/W1532651809","https://openalex.org/W1540155273","https://openalex.org/W1549083695","https://openalex.org/W1591116419","https://openalex.org/W1961095629","https://openalex.org/W1964321627","https://openalex.org/W1983496390","https://openalex.org/W1986964250","https://openalex.org/W1993014362","https://openalex.org/W1994855553","https://openalex.org/W2008732654","https://openalex.org/W2009799921","https://openalex.org/W2019245255","https://openalex.org/W2045057203","https://openalex.org/W2060477745","https://openalex.org/W2070262181","https://openalex.org/W2092535060","https://openalex.org/W2098699644","https://openalex.org/W2103096501","https://openalex.org/W2112447569","https://openalex.org/W2113606819","https://openalex.org/W2116022929","https://openalex.org/W2116836863","https://openalex.org/W2122378993","https://openalex.org/W2129812935","https://openalex.org/W2133848164","https://openalex.org/W2140245639","https://openalex.org/W2145889472","https://openalex.org/W2149652297","https://openalex.org/W2165797462","https://openalex.org/W2167164761","https://openalex.org/W2169579681","https://openalex.org/W2242953327","https://openalex.org/W2584047031","https://openalex.org/W2610617435","https://openalex.org/W2667144866","https://openalex.org/W2897484797","https://openalex.org/W2904284080","https://openalex.org/W2942519784","https://openalex.org/W2943495883","https://openalex.org/W2948753010","https://openalex.org/W2962772276","https://openalex.org/W2962905348","https://openalex.org/W2964178928","https://openalex.org/W2964342346","https://openalex.org/W2975585604","https://openalex.org/W2988415939","https://openalex.org/W2989985842","https://openalex.org/W3000240650","https://openalex.org/W3002335951","https://openalex.org/W3005236973","https://openalex.org/W3011735119","https://openalex.org/W3014226319","https://openalex.org/W3100876745","https://openalex.org/W3103193393","https://openalex.org/W4235713725","https://openalex.org/W4250589301","https://openalex.org/W6630414125","https://openalex.org/W6676727762","https://openalex.org/W6676903177"],"related_works":["https://openalex.org/W2018264451","https://openalex.org/W1015651293","https://openalex.org/W2591253179","https://openalex.org/W4287671600","https://openalex.org/W2953883784","https://openalex.org/W4212827636","https://openalex.org/W2141366819","https://openalex.org/W4322716129","https://openalex.org/W3004408979","https://openalex.org/W2151681302"],"abstract_inverted_index":{"Existing":[0],"Dictionary":[1],"Learning":[2],"and":[3,36,113,155,226,236],"Sparse":[4],"Coding":[5],"(DLSC)":[6],"algorithms":[7,230],"for":[8,70],"Symmetric":[9,64],"Positive":[10],"Definite":[11],"(SPD)":[12],"matrices":[13,168],"usually":[14],"adopt":[15],"Reproducing":[16],"Kernel":[17],"Hilbert":[18],"Space":[19,68],"as":[20,82,246],"workspace":[21,62],"to":[22,137,162,177,198],"perform":[23],"necessary":[24],"linear":[25,85,93,104],"operations.":[26,105],"But":[27],"those":[28],"methods":[29],"heavily":[30],"rely":[31],"on":[32,133,207],"ideal":[33],"kernel":[34],"maps":[35],"they":[37],"are":[38],"lack":[39],"of":[40,51,74,88,143,152,166,193,233,244],"robustness":[41],"when":[42],"facing":[43],"different":[44,224],"SPD":[45,75,89,114,145,167],"data,":[46,146],"especially":[47],"in":[48,108,120,123,169,231],"the":[49,83,139,150,174,189,201,242],"case":[50],"high-sparsity":[52,221],"coding.":[53],"Different":[54],"from":[55],"existing":[56],"methods,":[57],"we":[58],"explore":[59],"a":[60,92,97,126,156,247],"new":[61],"called":[63],"Matrices":[65],"Inner":[66],"Product":[67],"(SMIPS)":[69],"modeling":[71],"robust":[72,218],"DLSC":[73,107],"matrices.":[76],"SMIPS,":[77],"which":[78,172,239],"can":[79,116],"be":[80],"treated":[81],"minimal":[84],"expansion":[86],"space":[87,94],"manifold,":[90],"is":[91,110,135,160,196,216],"equipped":[95],"with":[96,220],"pre-defined":[98],"inner":[99],"product":[100],"so":[101,147],"it":[102],"supports":[103],"Modelling":[106],"SMIPS":[109,170,245],"more":[111,217],"intuitive,":[112],"data":[115],"preserve":[117],"matrix":[118,179],"form":[119,191],"SMIPS.":[121],"Then,":[122],"this":[124],"paper,":[125],"Riemannian":[127,140],"Geometry":[128],"Preserving":[129],"(RGP)":[130],"method":[131],"based":[132],"graph-regularized":[134],"proposed":[136,197],"include":[138],"geometric":[141],"information":[142],"original":[144],"that":[148,213],"improves":[149],"discriminability":[151],"sparse":[153,157,164],"codes,":[154],"coding":[158,222],"algorithm":[159,215],"developed":[161],"acquire":[163],"codes":[165,195],"efficiently,":[171],"extend":[173],"feature-sign":[175],"search":[176],"such":[178],"space.":[180],"For":[181],"dictionary":[182,203],"learning,":[183],"an":[184],"overall":[185],"learning":[186,204,237],"strategy":[187],"utilizing":[188],"closed":[190],"solution":[192],"RGP":[194],"speed":[199],"up":[200],"iterative":[202],"process.":[205],"Experiments":[206],"several":[208],"computer":[209],"vision":[210],"tasks":[211],"show":[212],"our":[214],"even":[219],"across":[223],"datasets":[225],"outperforms":[227],"other":[228],"comparative":[229],"terms":[232],"recognition":[234],"accuracy":[235],"efficiency,":[238],"also":[240],"demonstrates":[241],"validity":[243],"workspace.":[248]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}