{"id":"https://openalex.org/W3194814583","doi":"https://doi.org/10.1109/tnnls.2021.3105678","title":"Intrinsic Graph Learning With Discrete Constrained Diffusion\u2013Fusion","display_name":"Intrinsic Graph Learning With Discrete Constrained Diffusion\u2013Fusion","publication_year":2021,"publication_date":"2021-08-25","ids":{"openalex":"https://openalex.org/W3194814583","doi":"https://doi.org/10.1109/tnnls.2021.3105678","mag":"3194814583","pmid":"https://pubmed.ncbi.nlm.nih.gov/34432641"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3105678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3105678","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5019106042","display_name":"Xiaohui Wei","orcid":"https://orcid.org/0000-0001-5086-0103"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaohui Wei","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-5086-0103","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102716602","display_name":"Ting Lu","orcid":"https://orcid.org/0000-0001-8415-0185"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Lu","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-6744-2186","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067097659","display_name":"Shutao Li","orcid":"https://orcid.org/0000-0002-0585-9848"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shutao Li","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0585-9848","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019106042"],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09979156,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":"3","first_page":"1613","last_page":"1626"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9987000226974487,"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"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9955999851226807,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9947999715805054,"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/graph","display_name":"Graph","score":0.49906444549560547},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.49190306663513184},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48156359791755676},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.41764211654663086},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.357593834400177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3377317190170288},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.19945460557937622},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.08338689804077148},{"id":"https://openalex.org/keywords/thermodynamics","display_name":"Thermodynamics","score":0.061866194009780884},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.0576881468296051}],"concepts":[{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49906444549560547},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.49190306663513184},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48156359791755676},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.41764211654663086},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.357593834400177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3377317190170288},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.19945460557937622},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.08338689804077148},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.061866194009780884},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0576881468296051}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3105678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3105678","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:34432641","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34432641","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G102502481","display_name":null,"funder_award_id":"2021T140194","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G3183906717","display_name":null,"funder_award_id":"61906167","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6229004399","display_name":null,"funder_award_id":"61801179","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W45551751","https://openalex.org/W297461772","https://openalex.org/W1535602073","https://openalex.org/W1572158434","https://openalex.org/W1975172027","https://openalex.org/W1979089718","https://openalex.org/W1984776140","https://openalex.org/W1997201895","https://openalex.org/W2053186076","https://openalex.org/W2083666679","https://openalex.org/W2118382442","https://openalex.org/W2123432324","https://openalex.org/W2129793592","https://openalex.org/W2134529554","https://openalex.org/W2154872931","https://openalex.org/W2155904486","https://openalex.org/W2163605054","https://openalex.org/W2165874743","https://openalex.org/W2171964228","https://openalex.org/W2187089797","https://openalex.org/W2264350531","https://openalex.org/W2406581873","https://openalex.org/W2407812036","https://openalex.org/W2466939964","https://openalex.org/W2579597427","https://openalex.org/W2595272553","https://openalex.org/W2604723872","https://openalex.org/W2758611985","https://openalex.org/W2780643544","https://openalex.org/W2793357412","https://openalex.org/W2799712919","https://openalex.org/W2804847616","https://openalex.org/W2807021761","https://openalex.org/W2808241692","https://openalex.org/W2808858332","https://openalex.org/W2809368372","https://openalex.org/W2810594911","https://openalex.org/W2888654602","https://openalex.org/W2896169497","https://openalex.org/W2900980272","https://openalex.org/W2904125861","https://openalex.org/W2904176920","https://openalex.org/W2910457605","https://openalex.org/W2913960921","https://openalex.org/W2940933409","https://openalex.org/W2949195375","https://openalex.org/W2955147859","https://openalex.org/W2968392770","https://openalex.org/W2971297210","https://openalex.org/W2998358581","https://openalex.org/W3003326148","https://openalex.org/W3015899030","https://openalex.org/W3100848837","https://openalex.org/W6601786222","https://openalex.org/W6682644385","https://openalex.org/W6683379805","https://openalex.org/W6684578312","https://openalex.org/W6714133674","https://openalex.org/W6731811539","https://openalex.org/W6767861127","https://openalex.org/W6929385289"],"related_works":["https://openalex.org/W2099421762","https://openalex.org/W2530546662","https://openalex.org/W2967030268","https://openalex.org/W2185253430","https://openalex.org/W4210345652","https://openalex.org/W1984333081","https://openalex.org/W2945063165","https://openalex.org/W3188962172","https://openalex.org/W2205042400","https://openalex.org/W2090790166"],"abstract_inverted_index":{"Graphs":[0],"are":[1,72,134],"essential":[2],"to":[3,22,43,55,64,92,136,151,174,177,192,208],"improve":[4],"the":[5,45,51,58,94,106,112,115,121,126,138,145,164,167,171,178,188,193,211,218,237,242],"performance":[6],"of":[7,29,34,48,105,142,148,166,170,180,203,213],"graph-based":[8],"machine":[9],"learning":[10,33,86,205],"methods,":[11],"such":[12],"as":[13],"spectral":[14],"clustering.":[15],"Various":[16],"well-designed":[17],"methods":[18,53,240],"have":[19,230],"been":[20],"proposed":[21,234],"learn":[23],"graphs":[24,38,71,216],"that":[25,185,232],"depict":[26],"specific":[27],"properties":[28],"real-world":[30],"data.":[31],"Joint":[32],"knowledge":[35],"in":[36,97,217],"different":[37],"is":[39,77,206],"an":[40],"effective":[41],"means":[42],"uncover":[44],"intrinsic":[46,84],"structure":[47,66,119],"samples.":[49],"However,":[50],"existing":[52],"fail":[54],"simultaneously":[56],"mine":[57],"global":[59,116],"and":[60,67,74,157,196,226],"local":[61],"information":[62],"related":[63],"sample":[65,181],"distribution":[68],"when":[69],"multiple":[70],"available,":[73],"further":[75],"research":[76],"needed.":[78],"Hence,":[79],"we":[80],"propose":[81],"a":[82,103,200],"novel":[83],"graph":[85,113,173],"(IGL)":[87],"with":[88],"discrete":[89,132],"constrained":[90],"diffusion-fusion":[91,122],"solve":[93],"above":[95],"problem":[96],"this":[98],"article.":[99],"In":[100],"detail,":[101],"given":[102],"set":[104],"predefined":[107,215],"graphs,":[108],"IGL":[109],"first":[110],"obtains":[111],"encoding":[114],"high-order":[117],"manifold":[118],"via":[120],"mechanism":[123],"based":[124],"on":[125,223,241],"tensor":[127],"product":[128],"graph.":[129,140],"Then,":[130],"two":[131,227],"operators":[133],"integrated":[135],"fine-prune":[137],"obtained":[139,172],"One":[141],"them":[143],"limits":[144],"maximum":[146],"number":[147,179],"neighbors":[149],"connected":[150],"each":[152],"sample,":[153],"thereby":[154],"removing":[155],"redundant":[156],"erroneous":[158],"edges.":[159],"The":[160],"other":[161],"one":[162],"forces":[163],"rank":[165],"Laplacian":[168],"matrix":[169],"be":[175],"equal":[176],"clusters,":[182],"which":[183],"guarantees":[184],"samples":[186],"from":[187],"same":[189,194],"subgraph":[190],"belong":[191],"cluster":[195],"vice":[197],"versa.":[198],"Moreover,":[199],"new":[201],"strategy":[202],"weight":[204],"designed":[207],"accurately":[209],"quantify":[210],"contribution":[212],"pairwise":[214],"optimization":[219],"process.":[220],"Extensive":[221],"experiments":[222],"six":[224],"single-view":[225],"multiview":[228],"datasets":[229],"demonstrated":[231],"our":[233],"method":[235],"outperforms":[236],"previous":[238],"state-of-the-art":[239],"clustering":[243],"task.":[244]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}