{"id":"https://openalex.org/W3034209897","doi":"https://doi.org/10.1109/sam48682.2020.9104275","title":"POPLAR: Parafac2 decOmPosition using auxiLiAry infoRmation","display_name":"POPLAR: Parafac2 decOmPosition using auxiLiAry infoRmation","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3034209897","doi":"https://doi.org/10.1109/sam48682.2020.9104275","mag":"3034209897"},"language":"en","primary_location":{"id":"doi:10.1109/sam48682.2020.9104275","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sam48682.2020.9104275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","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/A5028367791","display_name":"Ekta Gujral","orcid":"https://orcid.org/0000-0001-7255-3374"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ekta Gujral","raw_affiliation_strings":["UC Riverside"],"affiliations":[{"raw_affiliation_string":"UC Riverside","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066303412","display_name":"Georgios Theocharous","orcid":null},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Georgios Theocharous","raw_affiliation_strings":["Adobe Inc"],"affiliations":[{"raw_affiliation_string":"Adobe Inc","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054849323","display_name":"Evangelos E. Papalexakis","orcid":"https://orcid.org/0000-0002-3411-8483"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Evangelos E. Papalexakis","raw_affiliation_strings":["UC Riverside"],"affiliations":[{"raw_affiliation_string":"UC Riverside","institution_ids":["https://openalex.org/I103635307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028367791"],"corresponding_institution_ids":["https://openalex.org/I103635307"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0675,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9980999827384949,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9474999904632568,"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-decomposition","display_name":"Tensor decomposition","score":0.7174294590950012},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.6481428146362305},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6229777932167053},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6003343462944031},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5492997169494629},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5334577560424805},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4369739592075348},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.360609769821167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3258630037307739},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3138695955276489},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.277824342250824}],"concepts":[{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.7174294590950012},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.6481428146362305},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6229777932167053},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6003343462944031},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5492997169494629},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5334577560424805},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4369739592075348},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.360609769821167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3258630037307739},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3138695955276489},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.277824342250824},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"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/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sam48682.2020.9104275","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sam48682.2020.9104275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","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":32,"referenced_works":["https://openalex.org/W1544449255","https://openalex.org/W1850275953","https://openalex.org/W1969116741","https://openalex.org/W1983623418","https://openalex.org/W2000215628","https://openalex.org/W2024165284","https://openalex.org/W2042775700","https://openalex.org/W2049588365","https://openalex.org/W2081051946","https://openalex.org/W2108119513","https://openalex.org/W2119741678","https://openalex.org/W2121154640","https://openalex.org/W2121433185","https://openalex.org/W2121739212","https://openalex.org/W2133787701","https://openalex.org/W2135496322","https://openalex.org/W2164278908","https://openalex.org/W2167838035","https://openalex.org/W2528907418","https://openalex.org/W2561915573","https://openalex.org/W2604652149","https://openalex.org/W2753916251","https://openalex.org/W2771685360","https://openalex.org/W2799295784","https://openalex.org/W2962702353","https://openalex.org/W2964343053","https://openalex.org/W3035671087","https://openalex.org/W4301912954","https://openalex.org/W6632433782","https://openalex.org/W6676321539","https://openalex.org/W6678233195","https://openalex.org/W6684379799"],"related_works":["https://openalex.org/W1973739845","https://openalex.org/W119752240","https://openalex.org/W4379256054","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"],"abstract_inverted_index":{"PARAFAC2":[0,51],"is":[1,45,61,118],"a":[2],"powerful":[3],"method":[4,20,44,117],"for":[5,49,115],"analyzing":[6],"multi-modal":[7],"data":[8],"consisting":[9],"of":[10,57],"irregular":[11],"frontal":[12],"slices.":[13],"In":[14],"this":[15],"work,":[16],"we":[17],"propose":[18],"POPLAR":[19,60,89],"that":[21],"imposes":[22],"graph":[23,67],"Laplacians":[24,68],"constraints":[25,69],"induced":[26],"by":[27],"the":[28,43,55,62,97,107,112,116,121],"similarity":[29],"symmetric":[30],"tensor":[31,52],"as":[32],"auxiliary":[33,71],"information":[34],"to":[35,39,65,80,96,120],"force":[36],"decomposition":[37],"factors":[38],"behave":[40],"similarly":[41],"and":[42,85,88,101],"developed":[46],"using":[47,70],"AO-ADMM":[48],"3-way":[50],"decomposition.":[53],"To":[54],"best":[56],"our":[58],"knowledge,":[59],"first":[63],"approach":[64],"incorporate":[66],"information.":[72],"We":[73],"extensively":[74],"evaluate":[75],"POPLAR's":[76],"performance":[77,93],"in":[78],"comparison":[79],"state-of-the-art":[81,108],"approaches":[82],"across":[83],"synthetic":[84],"real":[86],"dataset,":[87],"clearly":[90],"exhibits":[91],"better":[92],"with":[94],"respect":[95],"Fitness":[98],"(better":[99,104],"3-8%),":[100],"F1":[102],"score":[103],"5-20%)":[105],"among":[106],"factorization":[109],"method.":[110,123],"Furthermore,":[111],"running":[113],"time":[114],"comparable":[119],"state-of-art":[122]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}