{"id":"https://openalex.org/W3113954210","doi":"https://doi.org/10.23919/eusipco47968.2020.9287404","title":"Tensor Recovery via Nonconvex Low-Rank Approximation","display_name":"Tensor Recovery via Nonconvex Low-Rank Approximation","publication_year":2020,"publication_date":"2020-12-18","ids":{"openalex":"https://openalex.org/W3113954210","doi":"https://doi.org/10.23919/eusipco47968.2020.9287404","mag":"3113954210"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco47968.2020.9287404","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco47968.2020.9287404","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 28th European Signal Processing Conference (EUSIPCO)","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/A5100443704","display_name":"Lin Chen","orcid":"https://orcid.org/0000-0002-0907-3236"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Chen","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074129836","display_name":"Xue Jiang","orcid":"https://orcid.org/0000-0001-7099-6817"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Jiang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061319150","display_name":"Xingzhao Liu","orcid":"https://orcid.org/0000-0002-4533-3904"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingzhao Liu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101854736","display_name":"Zhixin Zhou","orcid":"https://orcid.org/0000-0003-3737-9248"},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixin Zhou","raw_affiliation_strings":["Space Engineering University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Space Engineering University, Beijing, China","institution_ids":["https://openalex.org/I4210148107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"710","last_page":"714"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9948999881744385,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9943000078201294,"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/logarithm","display_name":"Logarithm","score":0.7292710542678833},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6947669982910156},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.6754688620567322},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5918107628822327},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5825909972190857},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5415601134300232},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5113329291343689},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.45059168338775635},{"id":"https://openalex.org/keywords/convex-function","display_name":"Convex function","score":0.44360512495040894},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.4221823811531067},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4144544303417206},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.4142746031284332},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.4103230834007263},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3477177023887634},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.12580585479736328},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.12396153807640076},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.12159556150436401}],"concepts":[{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.7292710542678833},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6947669982910156},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.6754688620567322},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5918107628822327},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5825909972190857},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5415601134300232},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5113329291343689},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.45059168338775635},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.44360512495040894},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.4221823811531067},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4144544303417206},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.4142746031284332},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.4103230834007263},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3477177023887634},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.12580585479736328},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.12396153807640076},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.12159556150436401},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/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},{"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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco47968.2020.9287404","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco47968.2020.9287404","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 28th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2043571470","https://openalex.org/W2056532343","https://openalex.org/W2091449379","https://openalex.org/W2505029951","https://openalex.org/W2598601363","https://openalex.org/W2762772695","https://openalex.org/W2901836533","https://openalex.org/W2964214749","https://openalex.org/W2969860805","https://openalex.org/W2970580464","https://openalex.org/W3012080241","https://openalex.org/W4285719527","https://openalex.org/W6775638715"],"related_works":["https://openalex.org/W4221157149","https://openalex.org/W4283122425","https://openalex.org/W2106005123","https://openalex.org/W2057590040","https://openalex.org/W3135513863","https://openalex.org/W1991825408","https://openalex.org/W1507830821","https://openalex.org/W2969889343","https://openalex.org/W4306936641","https://openalex.org/W4382491871"],"abstract_inverted_index":{"The":[0],"low-rank":[1,28,94],"tensor":[2,53,82],"recovery":[3,29,147],"is":[4,73,87],"a":[5,33,51,77,103],"powerful":[6],"approach":[7],"to":[8,75,80,90,102],"depict":[9],"the":[10,39,43,57,63,69,81,92,98,114,122,127,131,145],"intrinsic":[11],"structure":[12],"within":[13],"high-dimensional":[14],"data,":[15],"and":[16,85,143],"has":[17],"been":[18],"extensively":[19],"leveraged":[20],"in":[21],"many":[22],"real-world":[23,132],"applications.":[24],"Conventional":[25],"techniques":[26],"of":[27,66,116,126,134],"formulate":[30],"it":[31],"as":[32,56],"rank":[34,40,59],"minimization":[35],"problem,":[36,106],"then":[37],"approximate":[38],"function":[41],"with":[42,62,113],"convex":[44,64],"relaxation.":[45],"In":[46,130],"this":[47],"paper,":[48],"we":[49,107],"propose":[50],"new":[52],"logarithmic":[54,71,99],"norm":[55,72,100],"nonconvex":[58,104],"surrogate.":[60],"Compared":[61],"surrogate":[65],"nuclear":[67],"norm,":[68],"proposed":[70,128],"proved":[74],"be":[76],"tighter":[78],"approximation":[79],"average":[83],"rank,":[84],"thus":[86],"more":[88],"sparsity-encouraging":[89],"extract":[91],"underlying":[93],"information.":[95],"Although":[96],"minimizing":[97],"leads":[101],"optimization":[105],"rigorously":[108],"derive":[109],"its":[110],"closed-form":[111],"solution":[112],"guarantee":[115],"local":[117],"optimality.":[118],"Experimental":[119],"results":[120],"demonstrate":[121],"strong":[123],"convergence":[124],"behavior":[125],"algorithm.":[129],"application":[133],"video":[135],"recovery,":[136],"our":[137],"method":[138],"outperforms":[139],"several":[140],"state-of-the-art":[141],"methods":[142],"shows":[144],"remarkable":[146],"accuracy.":[148]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}