{"id":"https://openalex.org/W4412170768","doi":"https://doi.org/10.1109/tsipn.2025.3588087","title":"RNGCNs: Robust Norm Graph Convolutional Networks in the Presence of Missing Data and Large Noises","display_name":"RNGCNs: Robust Norm Graph Convolutional Networks in the Presence of Missing Data and Large Noises","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412170768","doi":"https://doi.org/10.1109/tsipn.2025.3588087"},"language":"en","primary_location":{"id":"doi:10.1109/tsipn.2025.3588087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2025.3588087","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"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 Signal and Information Processing over Networks","raw_type":"journal-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/A5107520061","display_name":"Ziyan Zhang","orcid":"https://orcid.org/0000-0001-9429-1635"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziyan Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-9429-1635","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053609164","display_name":"Bo Jiang","orcid":"https://orcid.org/0000-0002-6238-1596"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Jiang","raw_affiliation_strings":["School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-6238-1596","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018878455","display_name":"Zhengzheng Tu","orcid":"https://orcid.org/0000-0002-9689-8657"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengzheng Tu","raw_affiliation_strings":["School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-9689-8657","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107117636","display_name":"Bin Luo","orcid":"https://orcid.org/0000-0002-1414-3307"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Luo","raw_affiliation_strings":["School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-1414-3307","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5107520061"],"corresponding_institution_ids":["https://openalex.org/I143868143"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0783101,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"859","last_page":"871"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994000196456909,"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/T10057","display_name":"Face and Expression Recognition","score":0.9975000023841858,"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/missing-data","display_name":"Missing data","score":0.5601906180381775},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.469585120677948},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4601894021034241},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44999420642852783},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.357458233833313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3384987711906433},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2452165186405182},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1576402187347412},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.06311580538749695},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.06114962697029114}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5601906180381775},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.469585120677948},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4601894021034241},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44999420642852783},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.357458233833313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3384987711906433},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2452165186405182},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1576402187347412},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.06311580538749695},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.06114962697029114}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsipn.2025.3588087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2025.3588087","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"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 Signal and Information Processing over Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6272629075","display_name":null,"funder_award_id":"62076004","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1963932623","https://openalex.org/W2053090063","https://openalex.org/W2088616581","https://openalex.org/W2100556411","https://openalex.org/W2101117936","https://openalex.org/W2113590298","https://openalex.org/W2115706991","https://openalex.org/W2126607811","https://openalex.org/W2135046866","https://openalex.org/W2149532724","https://openalex.org/W2153959628","https://openalex.org/W2161041254","https://openalex.org/W2162915993","https://openalex.org/W2166782149","https://openalex.org/W2558460151","https://openalex.org/W2560185252","https://openalex.org/W2943501111","https://openalex.org/W2949208225","https://openalex.org/W2963017945","https://openalex.org/W2964321699","https://openalex.org/W2964583308","https://openalex.org/W2966398094","https://openalex.org/W2979683452","https://openalex.org/W2998122931","https://openalex.org/W3040731923","https://openalex.org/W3092835783","https://openalex.org/W3094504436","https://openalex.org/W3111787430","https://openalex.org/W3114928288","https://openalex.org/W3152893301","https://openalex.org/W3211302945","https://openalex.org/W4205827254","https://openalex.org/W4318603849","https://openalex.org/W4321195244","https://openalex.org/W4365790424","https://openalex.org/W4382239624","https://openalex.org/W4382239927","https://openalex.org/W4385992284","https://openalex.org/W4391640608","https://openalex.org/W4393238102","https://openalex.org/W4394699149","https://openalex.org/W4406110705","https://openalex.org/W4409670707","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6637178625","https://openalex.org/W6679973066","https://openalex.org/W6682494755","https://openalex.org/W6719270105","https://openalex.org/W6726873649","https://openalex.org/W6736685754","https://openalex.org/W6738964360","https://openalex.org/W6746015598","https://openalex.org/W6748799445","https://openalex.org/W6748848838","https://openalex.org/W6754929296","https://openalex.org/W6771536047","https://openalex.org/W6776488958","https://openalex.org/W6779961489","https://openalex.org/W6784977419","https://openalex.org/W6797464607","https://openalex.org/W6802872360","https://openalex.org/W6803512735","https://openalex.org/W6804077179","https://openalex.org/W6804318920","https://openalex.org/W6853482260"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W4380150146","https://openalex.org/W3024870410","https://openalex.org/W2410652950","https://openalex.org/W1979597421","https://openalex.org/W4283773154","https://openalex.org/W3139174110","https://openalex.org/W4289597203","https://openalex.org/W2007980826","https://openalex.org/W2085630472"],"abstract_inverted_index":{"Graph":[0,86],"Convolutional":[1],"Networks":[2],"(GCNs)":[3],"have":[4],"been":[5],"widely":[6],"studied":[7],"for":[8,89,154],"attribute":[9],"graph":[10,16,33,49,80,90,155],"data":[11,50,91,156],"learning.":[12,157],"In":[13],"many":[14],"applications,":[15],"node":[17],"attributes/features":[18],"may":[19],"contain":[20],"various":[21],"kinds":[22,151],"of":[23,95,109,116,152,169],"noises,":[24],"such":[25],"as":[26],"gross":[27],"corruption":[28],"and":[29,54,82,98,149,167],"missing":[30,52,99],"values.":[31,100],"Existing":[32],"convolutions":[34],"(GCs)":[35],"generally":[36],"focus":[37],"on":[38,41,106,119,122,160],"feature":[39,61,76,96],"propagation":[40,113,134],"structured-graph":[42],"which":[43],"i)":[44],"fail":[45],"to":[46,59,72],"address":[47,64],"the":[48,93,107,141,165,170],"with":[51],"values":[53],"ii)":[55],"often":[56],"perform":[57],"susceptibility":[58],"large":[60],"errors/noises.":[62],"To":[63],"this":[65,68],"issue,":[66],"in":[67,92],"paper,":[69],"we":[70,124,139],"propose":[71,150],"incorporate":[73,140],"robust":[74,131],"norm":[75,132],"learning":[77],"mechanism":[78],"into":[79,136,144],"convolution":[81],"present":[83],"Robust":[84],"Norm":[85],"Convolutions":[87],"(RNGCs)":[88],"presence":[94],"noises":[97],"Our":[101],"RNGCs":[102,128,143],"are":[103],"proposed":[104,171],"based":[105,133],"interpretation":[108],"GCs":[110],"from":[111],"a":[112],"function":[114],"aspect":[115],"\u2018data":[117],"reconstruction":[118],"graph\u2019.":[120],"Based":[121],"it,":[123],"then":[125],"derive":[126],"our":[127],"by":[129],"exploiting":[130],"functions":[135],"GCs.":[137],"Finally,":[138],"derived":[142],"an":[145],"end-to-end":[146],"network":[147],"architecture":[148],"RNGCNs":[153],"Experimental":[158],"results":[159],"several":[161],"noisy":[162],"datasets":[163],"demonstrate":[164],"effectiveness":[166],"robustness":[168],"RNGCNs.":[172]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
