{"id":"https://openalex.org/W3015546786","doi":"https://doi.org/10.1109/icassp40776.2020.9054312","title":"Weighted Krylov-Levenberg-Marquardt Method for Canonical Polyadic Tensor Decomposition","display_name":"Weighted Krylov-Levenberg-Marquardt Method for Canonical Polyadic Tensor Decomposition","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015546786","doi":"https://doi.org/10.1109/icassp40776.2020.9054312","mag":"3015546786"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054312","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 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/A5076229848","display_name":"Petr Tichavsk\u00fd","orcid":"https://orcid.org/0000-0003-0621-4766"},"institutions":[{"id":"https://openalex.org/I4210119419","display_name":"Czech Academy of Sciences, Institute of Information Theory and Automation","ror":"https://ror.org/03h1hsz49","country_code":"CZ","type":"facility","lineage":["https://openalex.org/I202391551","https://openalex.org/I4210119419"]}],"countries":["CZ"],"is_corresponding":true,"raw_author_name":"Petr Tichavsky","raw_affiliation_strings":["The Czech Academy of Sciences, Institute of Information Theory and Automation, Czech Republic"],"affiliations":[{"raw_affiliation_string":"The Czech Academy of Sciences, Institute of Information Theory and Automation, Czech Republic","institution_ids":["https://openalex.org/I4210119419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052051065","display_name":"Anh Huy Phan","orcid":"https://orcid.org/0000-0002-5509-7773"},"institutions":[{"id":"https://openalex.org/I125989756","display_name":"Skolkovo Institute of Science and Technology","ror":"https://ror.org/03f9nc143","country_code":"RU","type":"education","lineage":["https://openalex.org/I125989756"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Anh-Huy Phan","raw_affiliation_strings":["Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia"],"affiliations":[{"raw_affiliation_string":"Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia","institution_ids":["https://openalex.org/I125989756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018676117","display_name":"Andrzej Cichocki","orcid":"https://orcid.org/0000-0002-8364-7226"},"institutions":[{"id":"https://openalex.org/I125989756","display_name":"Skolkovo Institute of Science and Technology","ror":"https://ror.org/03f9nc143","country_code":"RU","type":"education","lineage":["https://openalex.org/I125989756"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Andrzej Cichocki","raw_affiliation_strings":["Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia"],"affiliations":[{"raw_affiliation_string":"Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia","institution_ids":["https://openalex.org/I125989756"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076229848"],"corresponding_institution_ids":["https://openalex.org/I4210119419"],"apc_list":null,"apc_paid":null,"fwci":0.7056,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.62762022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"vii","issue":null,"first_page":"3917","last_page":"3921"},"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9556999802589417,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9524999856948853,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/levenberg\u2013marquardt-algorithm","display_name":"Levenberg\u2013Marquardt algorithm","score":0.7726054191589355},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6416499614715576},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6297490000724792},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.6256605982780457},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5898218154907227},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5347496867179871},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.4860961437225342},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4831671118736267},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4793584942817688},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.47073686122894287},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4576079547405243},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.42173996567726135},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3703119158744812},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24311542510986328},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1890764832496643},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.08345106244087219}],"concepts":[{"id":"https://openalex.org/C87578567","wikidata":"https://www.wikidata.org/wiki/Q1426494","display_name":"Levenberg\u2013Marquardt algorithm","level":3,"score":0.7726054191589355},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6416499614715576},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6297490000724792},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.6256605982780457},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5898218154907227},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5347496867179871},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.4860961437225342},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4831671118736267},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4793584942817688},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.47073686122894287},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4576079547405243},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42173996567726135},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3703119158744812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24311542510986328},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1890764832496643},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.08345106244087219},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9054312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054312","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W10350632","https://openalex.org/W649715400","https://openalex.org/W1682665945","https://openalex.org/W1989811026","https://openalex.org/W2008972618","https://openalex.org/W2024165284","https://openalex.org/W2028273200","https://openalex.org/W2030790903","https://openalex.org/W2043342740","https://openalex.org/W2066392792","https://openalex.org/W2282347063","https://openalex.org/W2469230926","https://openalex.org/W2775111227","https://openalex.org/W2899051391","https://openalex.org/W2904192238","https://openalex.org/W2944211990","https://openalex.org/W2945335377","https://openalex.org/W2975201891","https://openalex.org/W2983221284","https://openalex.org/W4248478717","https://openalex.org/W6762536117"],"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":{"Weighted":[0],"canonical":[1],"polyadic":[2],"(CP)":[3],"tensor":[4,25,44],"decomposition":[5,19,54,94],"appears":[6],"in":[7,35,92,102,113],"a":[8,46],"wide":[9],"range":[10],"of":[11],"applications.":[12],"A":[13],"typical":[14],"situation":[15],"where":[16],"the":[17,30,36,40,43,105],"weighted":[18],"is":[20,22,32],"needed":[21],"when":[23],"some":[24,114],"elements":[26,38],"are":[27,56],"unknown,":[28],"and":[29],"task":[31],"to":[33,87],"fill":[34],"missing":[37],"under":[39],"assumption":[41],"that":[42,104],"admits":[45],"low-rank":[47],"model.":[48],"The":[49,82],"traditional":[50],"methods":[51,61,66],"for":[52],"large-scale":[53,93],"tasks":[55],"based":[57],"on":[58,79],"alternating":[59],"least-squares":[60],"or":[62,97],"gradient":[63],"methods.":[64],"Second-order":[65],"might":[67],"have":[68],"significantly":[69],"better":[70],"convergence,":[71],"but":[72],"so":[73],"far":[74],"they":[75],"were":[76],"used":[77],"only":[78],"small":[80],"tensors.":[81],"proposed":[83,106],"Krylov-Levenberg-Marquardt":[84],"method":[85],"enables":[86],"do":[88],"second-order-based":[89],"iterations":[90],"even":[91],"problems,":[95],"with":[96],"without":[98],"weights.":[99],"We":[100],"show":[101],"simulations":[103],"technique":[107],"can":[108],"outperform":[109],"existing":[110],"state-of-the-art":[111],"algorithms":[112],"scenarios.":[115]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}