{"id":"https://openalex.org/W4411232083","doi":"https://doi.org/10.1109/tsp.2025.3577762","title":"Slim Is Better: Transform-Based Tensor Robust Principal Component Analysis","display_name":"Slim Is Better: Transform-Based Tensor Robust Principal Component Analysis","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411232083","doi":"https://doi.org/10.1109/tsp.2025.3577762"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2025.3577762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2025.3577762","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-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/A5100443761","display_name":"Lin Chen","orcid":"https://orcid.org/0000-0002-7036-151X"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lin Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447677","display_name":"Li Ge","orcid":"https://orcid.org/0000-0002-1922-4464"},"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":"Li Ge","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, 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":["School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365817","display_name":"Hongbin Li","orcid":"https://orcid.org/0000-0003-1453-847X"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongbin Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004533757","display_name":"Martin Haardt","orcid":"https://orcid.org/0000-0001-7810-975X"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Haardt","raw_affiliation_strings":["Communications Research Laboratory, Ilmenau University of Technology, Ilmenau, Germany"],"affiliations":[{"raw_affiliation_string":"Communications Research Laboratory, Ilmenau University of Technology, Ilmenau, Germany","institution_ids":["https://openalex.org/I119449181"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100443761"],"corresponding_institution_ids":["https://openalex.org/I108468826"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13534483,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"73","issue":null,"first_page":"2320","last_page":"2335"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9775999784469604,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9775999784469604,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.955299973487854,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9523000121116638,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/principal-component-analysis","display_name":"Principal component analysis","score":0.7358344793319702},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48054438829421997},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.47747278213500977},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.44138282537460327},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3994281589984894},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37816572189331055},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34059786796569824},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.14506232738494873}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7358344793319702},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48054438829421997},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.47747278213500977},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.44138282537460327},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3994281589984894},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37816572189331055},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34059786796569824},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.14506232738494873},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2025.3577762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2025.3577762","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1965125844","https://openalex.org/W1992426838","https://openalex.org/W2043571470","https://openalex.org/W2074682976","https://openalex.org/W2081926135","https://openalex.org/W2091449379","https://openalex.org/W2103972604","https://openalex.org/W2123921160","https://openalex.org/W2126607811","https://openalex.org/W2139208832","https://openalex.org/W2145962650","https://openalex.org/W2146634731","https://openalex.org/W2160664759","https://openalex.org/W2166163936","https://openalex.org/W2963107235","https://openalex.org/W2963328634","https://openalex.org/W2963885538","https://openalex.org/W2970580464","https://openalex.org/W2972366341","https://openalex.org/W2998391154","https://openalex.org/W3011789951","https://openalex.org/W3016388692","https://openalex.org/W3072262295","https://openalex.org/W3133902371","https://openalex.org/W3134651463","https://openalex.org/W3168052222","https://openalex.org/W3173732000","https://openalex.org/W3198865231","https://openalex.org/W3209566058","https://openalex.org/W4225816429","https://openalex.org/W4285154423","https://openalex.org/W4292363360","https://openalex.org/W4311278207","https://openalex.org/W4313153376","https://openalex.org/W4313251434","https://openalex.org/W4380607122","https://openalex.org/W4383503973","https://openalex.org/W4400525040","https://openalex.org/W6631190155","https://openalex.org/W6760637997","https://openalex.org/W6862065737"],"related_works":["https://openalex.org/W2373052636","https://openalex.org/W4283792950","https://openalex.org/W2033914206","https://openalex.org/W2124460284","https://openalex.org/W2042327336","https://openalex.org/W2563483704","https://openalex.org/W3124370832","https://openalex.org/W3003801099","https://openalex.org/W2003667605","https://openalex.org/W62130100"],"abstract_inverted_index":{"This":[0,157],"paper":[1],"addresses":[2],"the":[3,16,19,26,40,44,72,106,111,120,172],"tensor":[4,37,47,91,134,181],"robust":[5],"principal":[6],"component":[7],"analysis":[8,117],"(RPCA)":[9],"by":[10],"employing":[11],"linear":[12,83],"slim":[13,29,45,84,98,121],"transforms":[14,30,99],"along":[15],"mode-3":[17,82],"of":[18,28,127,175],"tensor.":[20],"Previous":[21],"works":[22],"have":[23],"empirically":[24],"shown":[25],"superiority":[27],"over":[31,177],"traditional":[32],"square":[33,140,155,179],"ones":[34],"in":[35],"low-rank":[36],"recovery.":[38],"However,":[39],"recovery":[41,73,148],"guarantee":[42,74],"for":[43,75,150],"transform-based":[46,180],"RPCA":[48],"(SRPCA)":[49],"remains":[50],"an":[51,130],"unresolved":[52],"issue,":[53],"as":[54],"existing":[55,107],"guarantees":[56],"are":[57,94],"only":[58],"applicable":[59,79],"to":[60,80,96,105,110,144,153],"invertible,":[61],"inner":[62],"product":[63],"preserving,":[64],"and":[65,100,167],"self-adjoint":[66],"transforms.":[67],"In":[68],"contrast,":[69],"we":[70],"establish":[71],"SRPCA":[76,151,176],"that":[77,119],"is":[78,159],"any":[81],"transform":[85,122],"under":[86],"certain":[87],"conditions.":[88],"Specifically,":[89],"new":[90],"incoherence":[92,135],"conditions":[93,108],"deduced":[95],"accommodate":[97],"can":[101],"also":[102],"be":[103],"simplified":[104],"pertaining":[109],"discrete":[112],"Fourier":[113],"transform.":[114],"Our":[115],"theoretical":[116],"reveals":[118],"with":[123],"a":[124,145],"condition":[125],"number":[126],"1":[128],"enjoys":[129],"averaging":[131],"effect":[132],"on":[133,164],"parameters":[136],"through":[137,161],"its":[138,154],"composing":[139],"transforms,":[141],"thus":[142],"leading":[143],"more":[146],"relaxed":[147],"bound":[149],"compared":[152],"counterparts.":[156],"insight":[158],"validated":[160],"experimental":[162],"results":[163],"both":[165],"synthetic":[166],"real":[168],"data,":[169],"which":[170],"demonstrate":[171],"improved":[173],"performance":[174],"traditionally":[178],"RPCA.":[182]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}