{"id":"https://openalex.org/W4372260555","doi":"https://doi.org/10.1109/icassp49357.2023.10094847","title":"Non-Convex Approaches for Low-Rank Tensor Completion under Tubal Sampling","display_name":"Non-Convex Approaches for Low-Rank Tensor Completion under Tubal Sampling","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372260555","doi":"https://doi.org/10.1109/icassp49357.2023.10094847"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10094847","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10094847","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"preprint","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/A5079034157","display_name":"Zheng Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zheng Tan","raw_affiliation_strings":["University of California,Los Angeles","University of California, Los Angeles"],"affiliations":[{"raw_affiliation_string":"University of California,Los Angeles","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"University of California, Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035286718","display_name":"Longxiu Huang","orcid":"https://orcid.org/0000-0002-6610-9653"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Longxiu Huang","raw_affiliation_strings":["Michigan State University"],"affiliations":[{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103070466","display_name":"HanQin Cai","orcid":"https://orcid.org/0000-0002-2937-1986"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"HanQin Cai","raw_affiliation_strings":["University of Central Florida"],"affiliations":[{"raw_affiliation_string":"University of Central Florida","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062067602","display_name":"Yifei Lou","orcid":"https://orcid.org/0000-0003-1973-5704"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yifei Lou","raw_affiliation_strings":["University of Texas at Dallas"],"affiliations":[{"raw_affiliation_string":"University of Texas at Dallas","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079034157"],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":0.33600649,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.43963099,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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/T12303","display_name":"Tensor decomposition and applications","score":0.9990000128746033,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9937999844551086,"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/tensor","display_name":"Tensor (intrinsic definition)","score":0.6555513739585876},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6263139247894287},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5597843527793884},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4961279332637787},{"id":"https://openalex.org/keywords/inpainting","display_name":"Inpainting","score":0.4366166591644287},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42725154757499695},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.4241790473461151},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.406653493642807},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3919035792350769},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.33362916111946106},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3241771459579468},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.2820165753364563},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.19570645689964294},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.13869529962539673}],"concepts":[{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6555513739585876},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6263139247894287},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5597843527793884},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4961279332637787},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.4366166591644287},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42725154757499695},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.4241790473461151},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.406653493642807},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3919035792350769},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33362916111946106},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3241771459579468},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.2820165753364563},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.19570645689964294},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.13869529962539673},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10094847","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10094847","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1922005389","https://openalex.org/W1991857131","https://openalex.org/W1998269045","https://openalex.org/W2030927653","https://openalex.org/W2043571470","https://openalex.org/W2089106993","https://openalex.org/W2164278908","https://openalex.org/W2508935523","https://openalex.org/W2600538886","https://openalex.org/W2611328865","https://openalex.org/W2762772695","https://openalex.org/W2767962166","https://openalex.org/W2962708900","https://openalex.org/W2963328634","https://openalex.org/W2963885538","https://openalex.org/W2963960715","https://openalex.org/W2964321615","https://openalex.org/W2971963065","https://openalex.org/W2996534391","https://openalex.org/W2997965215","https://openalex.org/W3123648408","https://openalex.org/W3128326574","https://openalex.org/W3134139903","https://openalex.org/W3137950938","https://openalex.org/W4226424852","https://openalex.org/W4318052082","https://openalex.org/W4360752541","https://openalex.org/W6684379799","https://openalex.org/W6789119005","https://openalex.org/W6791838475","https://openalex.org/W6842235982"],"related_works":["https://openalex.org/W2950186459","https://openalex.org/W2170114491","https://openalex.org/W2897298721","https://openalex.org/W2242624680","https://openalex.org/W2136127937","https://openalex.org/W4290987221","https://openalex.org/W2216309014","https://openalex.org/W2569661359","https://openalex.org/W3199841771","https://openalex.org/W4286971555"],"abstract_inverted_index":{"Tensor":[0],"completion":[1,30,50,96],"is":[2],"an":[3],"important":[4],"problem":[5],"in":[6,85,98],"modern":[7],"data":[8,63],"analysis.":[9],"In":[10],"this":[11],"work,":[12],"we":[13],"investigate":[14],"a":[15,65,73,86],"specific":[16],"sampling":[17,88],"strategy,":[18],"referred":[19],"to":[20,35],"as":[21],"tubal":[22],"sampling.":[23],"We":[24,54],"propose":[25],"two":[26,83],"novel":[27],"non-convex":[28],"tensor":[29,38,49],"frameworks":[31],"that":[32],"are":[33],"easy":[34],"implement,":[36],"named":[37],"L":[39],"<inf":[40,44],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[41,45],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</inf>":[42],"-L":[43],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</inf>":[46],"(TL12)":[47],"and":[48,64,78],"via":[51],"CUR":[52],"(TCCUR).":[53],"test":[55],"the":[56,76],"efficiency":[57,80],"of":[58,81,91],"both":[59],"methods":[60,84,97],"on":[61],"synthetic":[62],"color":[66],"image":[67],"inpainting":[68],"problem.":[69],"Empirical":[70],"results":[71],"reveal":[72],"trade-off":[74],"between":[75],"accuracy":[77],"time":[79],"these":[82],"low":[87],"ratio.":[89],"Each":[90],"them":[92],"outperforms":[93],"some":[94],"classical":[95],"at":[99],"least":[100],"one":[101],"aspect.":[102]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2023-05-07T00:00:00"}