{"id":"https://openalex.org/W3188662227","doi":"https://doi.org/10.1145/3469678.3469691","title":"L1/2 Regularization-Based Deep Incremental Non-negative Matrix Factorization for Tumor Recognition","display_name":"L1/2 Regularization-Based Deep Incremental Non-negative Matrix Factorization for Tumor Recognition","publication_year":2021,"publication_date":"2021-07-20","ids":{"openalex":"https://openalex.org/W3188662227","doi":"https://doi.org/10.1145/3469678.3469691","mag":"3188662227"},"language":"en","primary_location":{"id":"doi:10.1145/3469678.3469691","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469678.3469691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Fifth International Conference on Biological Information and Biomedical Engineering","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/A5048901609","display_name":"Lulu Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lulu Yan","raw_affiliation_strings":["Henan University, China"],"affiliations":[{"raw_affiliation_string":"Henan University, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101514016","display_name":"Xiaohui Yang","orcid":"https://orcid.org/0000-0002-6423-6798"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohui Yang","raw_affiliation_strings":["Henan University, China"],"affiliations":[{"raw_affiliation_string":"Henan University, China","institution_ids":["https://openalex.org/I173899330"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048901609"],"corresponding_institution_ids":["https://openalex.org/I173899330"],"apc_list":null,"apc_paid":null,"fwci":0.1609,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.48535256,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11213","display_name":"Genomic variations and chromosomal abnormalities","score":0.9828000068664551,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9703999757766724,"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/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.8618765473365784},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.7353873252868652},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.7279225587844849},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6707091331481934},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6648693084716797},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5899136066436768},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5750402212142944},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5491422414779663},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5374119877815247},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4941881000995636},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46386757493019104},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4174479842185974},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4130805730819702},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3538714051246643}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.8618765473365784},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7353873252868652},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.7279225587844849},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6707091331481934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6648693084716797},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5899136066436768},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5750402212142944},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5491422414779663},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5374119877815247},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4941881000995636},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46386757493019104},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4174479842185974},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4130805730819702},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3538714051246643},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3469678.3469691","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469678.3469691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Fifth International Conference on Biological Information and Biomedical Engineering","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":34,"referenced_works":["https://openalex.org/W1902027874","https://openalex.org/W1963666769","https://openalex.org/W1966701961","https://openalex.org/W1969900471","https://openalex.org/W1993335538","https://openalex.org/W1997413314","https://openalex.org/W2022604714","https://openalex.org/W2027459889","https://openalex.org/W2028781966","https://openalex.org/W2041891835","https://openalex.org/W2064208261","https://openalex.org/W2075103606","https://openalex.org/W2078481172","https://openalex.org/W2087684630","https://openalex.org/W2109363337","https://openalex.org/W2110798204","https://openalex.org/W2116216716","https://openalex.org/W2119792302","https://openalex.org/W2128985829","https://openalex.org/W2135035984","https://openalex.org/W2136155797","https://openalex.org/W2146913572","https://openalex.org/W2155653793","https://openalex.org/W2168784386","https://openalex.org/W2296359181","https://openalex.org/W2554355036","https://openalex.org/W2612696227","https://openalex.org/W2741258122","https://openalex.org/W2757241815","https://openalex.org/W2763089461","https://openalex.org/W2916995168","https://openalex.org/W3003536703","https://openalex.org/W4246697467","https://openalex.org/W6680012447"],"related_works":["https://openalex.org/W2127243424","https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W1995622179","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W4294224199"],"abstract_inverted_index":{"Non-negative":[0],"matrix":[1],"factorization":[2],"(NMF)":[3],"is":[4,29,36,59,77,93,104,118,123,138],"an":[5],"effective":[6],"technique":[7],"for":[8,21,140],"feature":[9],"representation":[10,117],"learning":[11,76,122],"and":[12,114,159],"dimensionality":[13],"reduction.":[14],"However,":[15],"there":[16],"are":[17],"two":[18],"critical":[19],"challenges":[20],"improving":[22],"the":[23,30,34,37,40,44,49,55,64,67,81,84,127,152,157],"performance":[24,50],"of":[25,32,43,51,66,83,131],"NMF-based":[26],"methods.":[27,161],"One":[28],"sparsity":[31,65],"representation,":[33],"other":[35],"sensitivity":[38],"to":[39,62,79,125],"initial":[41,85],"value":[42,86],"iteration,":[45],"which":[46,137],"seriously":[47],"affects":[48],"NMF.":[52],"To":[53],"solve":[54],"problems,":[56],"L1/2":[57,98],"regularization":[58],"skillfully":[60],"selected":[61],"characterize":[63],"data.":[68],"Furthermore,":[69],"a":[70,97,111],"layer-wise":[71],"pre-training":[72],"strategy":[73],"in":[74,106],"deep":[75,100,116],"used":[78],"alleviate":[80],"effect":[82],"on":[87,145],"NMF,":[88],"whereby":[89],"complex":[90],"network":[91],"structure":[92],"avoided.":[94],"As":[95],"such,":[96],"regularization-based":[99],"NMF":[101],"(L1/2-DNMF)":[102],"model":[103,155],"proposed":[105,153],"this":[107],"study,":[108],"such":[109],"that":[110,151],"more":[112],"stable":[113],"sparse":[115],"obtained.":[119],"Moreover,":[120],"incremental":[121],"introduced":[124],"reduce":[126],"high":[128],"computational":[129],"complexity":[130],"L1/2-DNMF":[132],"model,":[133,136],"called":[134],"L1/2-DINMF":[135,154],"suitable":[139],"online":[141],"processing.":[142],"Experiment":[143],"results":[144],"genetic":[146],"data-based":[147],"tumor":[148],"recognition":[149],"verify":[150],"outperforms":[156],"classic":[158],"state-of-the-art":[160]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}