{"id":"https://openalex.org/W3161814045","doi":"https://doi.org/10.1109/icassp39728.2021.9413637","title":"Tensor Decomposition Via Core Tensor Networks","display_name":"Tensor Decomposition Via Core Tensor Networks","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3161814045","doi":"https://doi.org/10.1109/icassp39728.2021.9413637","mag":"3161814045"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9413637","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413637","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-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/A5100395004","display_name":"Jianfu Zhang","orcid":"https://orcid.org/0000-0002-2673-5860"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]},{"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","JP"],"is_corresponding":true,"raw_author_name":"Jianfu ZHANG","raw_affiliation_strings":["RIKEN AIP","Shanghai Jiao Tong University"],"affiliations":[{"raw_affiliation_string":"RIKEN AIP","institution_ids":["https://openalex.org/I4210126580"]},{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053807025","display_name":"Zerui Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]},{"id":"https://openalex.org/I92614990","display_name":"Tokyo University of Agriculture and Technology","ror":"https://ror.org/00qg0kr10","country_code":"JP","type":"education","lineage":["https://openalex.org/I92614990"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"ZERUI TAO","raw_affiliation_strings":["RIKEN AIP","Tokyo University of Agriculture and Technology"],"affiliations":[{"raw_affiliation_string":"RIKEN AIP","institution_ids":["https://openalex.org/I4210126580"]},{"raw_affiliation_string":"Tokyo University of Agriculture and Technology","institution_ids":["https://openalex.org/I92614990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100741568","display_name":"Liqing Zhang","orcid":"https://orcid.org/0000-0001-7597-8503"},"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":"LIQING ZHANG","raw_affiliation_strings":["Shanghai Jiao Tong University"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083182987","display_name":"Qibin Zhao","orcid":"https://orcid.org/0000-0002-4442-3182"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"QIBIN ZHAO","raw_affiliation_strings":["RIKEN AIP"],"affiliations":[{"raw_affiliation_string":"RIKEN AIP","institution_ids":["https://openalex.org/I4210126580"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100395004"],"corresponding_institution_ids":["https://openalex.org/I183067930","https://openalex.org/I4210126580"],"apc_list":null,"apc_paid":null,"fwci":0.2683,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.43409915,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2130","last_page":"2134"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9422000050544739,"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/initialization","display_name":"Initialization","score":0.8498923778533936},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.7818090915679932},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6096735000610352},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5559543967247009},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5308260321617126},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.513664186000824},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.49003469944000244},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43089064955711365},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4087807536125183},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3454892635345459},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.33605629205703735}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.8498923778533936},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.7818090915679932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6096735000610352},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5559543967247009},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5308260321617126},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.513664186000824},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.49003469944000244},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43089064955711365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4087807536125183},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3454892635345459},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33605629205703735},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp39728.2021.9413637","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413637","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1814521481","https://openalex.org/W1908400401","https://openalex.org/W1963826206","https://openalex.org/W1993482030","https://openalex.org/W2000215628","https://openalex.org/W2024165284","https://openalex.org/W2080843093","https://openalex.org/W2103751387","https://openalex.org/W2121739212","https://openalex.org/W2147512299","https://openalex.org/W2176412452","https://openalex.org/W2431890537","https://openalex.org/W2604763608","https://openalex.org/W2741137940","https://openalex.org/W2754084392","https://openalex.org/W2789223439","https://openalex.org/W2795900505","https://openalex.org/W2914231700","https://openalex.org/W2923380536","https://openalex.org/W2962708900","https://openalex.org/W2962766718","https://openalex.org/W2963048316","https://openalex.org/W2963285578","https://openalex.org/W2963293339","https://openalex.org/W2963425582","https://openalex.org/W2964010806","https://openalex.org/W2964229782","https://openalex.org/W2965446129","https://openalex.org/W4294646197","https://openalex.org/W6639732408","https://openalex.org/W6675606679","https://openalex.org/W6679667936","https://openalex.org/W6685562342","https://openalex.org/W6717575008","https://openalex.org/W6736057607","https://openalex.org/W6748780714","https://openalex.org/W6750254146"],"related_works":["https://openalex.org/W4379256054","https://openalex.org/W2782704695","https://openalex.org/W2093953080","https://openalex.org/W2911706637","https://openalex.org/W47805180","https://openalex.org/W3216281372","https://openalex.org/W2963838862","https://openalex.org/W2608089480","https://openalex.org/W3015641590","https://openalex.org/W2987657992"],"abstract_inverted_index":{"Tensor":[0],"decomposition":[1],"(TD)":[2],"has":[3],"shown":[4],"promising":[5],"performance":[6],"in":[7,52,167],"image":[8],"completion":[9],"and":[10,55,111,152,171],"denoising.":[11],"Existing":[12],"methods":[13,166],"always":[14],"aim":[15],"to":[16,69,77,106,115,148],"decompose":[17,116],"one":[18],"tensor":[19,36,120,141],"into":[20],"latent":[21,78],"factors":[22],"or":[23,93],"core":[24,79,140],"tensors":[25,76,89],"by":[26],"optimizing":[27],"a":[28,34,71,101,117],"particular":[29],"cost":[30],"function":[31],"based":[32,132],"on":[33,133],"specific":[35],"model.":[37],"These":[38],"algorithms":[39],"iteratively":[40],"learn":[41,70],"the":[42,82,85,108,125,138,157],"optima":[43],"from":[44,74],"random":[45],"initialization":[46],"given":[47,119],"any":[48],"individual":[49],"tensor,":[50],"resulting":[51],"slow":[53],"convergence":[54],"low":[56],"efficiency.":[57,123],"In":[58],"this":[59,97],"paper,":[60],"we":[61,99],"propose":[62],"an":[63],"efficient":[64],"TD":[65,150,165],"algorithm":[66],"that":[67,84],"aims":[68],"global":[72,109],"mapping":[73,110],"input":[75],"tensors,":[80],"under":[81],"assumption":[83],"mappings":[86],"of":[87,128,160,169],"multiple":[88],"might":[90],"be":[91],"shared":[92],"highly":[94],"correlated.":[95],"To":[96],"end,":[98],"train":[100],"deep":[102],"neural":[103],"network":[104],"(DNN)":[105],"model":[107],"then":[112],"apply":[113],"it":[114],"newly":[118],"with":[121],"high":[122],"Furthermore,":[124],"initial":[126],"values":[127],"DNN":[129],"are":[130],"learned":[131],"meta-learning":[134],"methods.":[135],"By":[136],"leveraging":[137],"pretrained":[139],"DNN,":[142],"our":[143,161],"proposed":[144],"method":[145,162],"enables":[146],"us":[147],"perform":[149],"efficiently":[151],"accurately.":[153],"Experimental":[154],"results":[155],"demonstrate":[156],"significant":[158],"improvements":[159],"over":[163],"other":[164],"terms":[168],"speed":[170],"accuracy.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
