{"id":"https://openalex.org/W4392903716","doi":"https://doi.org/10.1109/icassp48485.2024.10448367","title":"Noise-Resistant Graph Neural Network for Node Classification","display_name":"Noise-Resistant Graph Neural Network for Node Classification","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392903716","doi":"https://doi.org/10.1109/icassp48485.2024.10448367"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10448367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10448367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 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/A5052622245","display_name":"Zichao Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]},{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN","SG"],"is_corresponding":true,"raw_author_name":"Zichao Deng","raw_affiliation_strings":["Nanyang Technological University (NTU),School of Computer Science and Engineering,Singapore","School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore","Alibaba-NTU Singapore Joint Research Institute, NTU, Singapore","Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University (NTU),School of Computer Science and Engineering,Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Alibaba-NTU Singapore Joint Research Institute, NTU, Singapore","institution_ids":[]},{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064069283","display_name":"Han Yu","orcid":"https://orcid.org/0000-0001-6893-8650"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Han Yu","raw_affiliation_strings":["Nanyang Technological University (NTU),School of Computer Science and Engineering,Singapore","School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University (NTU),School of Computer Science and Engineering,Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5052622245"],"corresponding_institution_ids":["https://openalex.org/I172675005","https://openalex.org/I45928872"],"apc_list":null,"apc_paid":null,"fwci":0.7301,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.73142588,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"7560","last_page":"7564"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9998999834060669,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9998999834060669,"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":0.995199978351593,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9902999997138977,"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/computer-science","display_name":"Computer science","score":0.8331168293952942},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6464464664459229},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6342185735702515},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5753116607666016},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5013811588287354},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.47429636120796204},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4679713845252991},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46199727058410645},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4136071503162384},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37019070982933044},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2004581093788147}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8331168293952942},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6464464664459229},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6342185735702515},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5753116607666016},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5013811588287354},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.47429636120796204},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4679713845252991},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46199727058410645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4136071503162384},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37019070982933044},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2004581093788147},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp48485.2024.10448367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10448367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320320766","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2622100130","https://openalex.org/W2900470550","https://openalex.org/W2963735582","https://openalex.org/W2964274690","https://openalex.org/W3034185248","https://openalex.org/W3042609801","https://openalex.org/W3166215705","https://openalex.org/W3204453541","https://openalex.org/W4287726895","https://openalex.org/W4312601326","https://openalex.org/W6726873649","https://openalex.org/W6732696085","https://openalex.org/W6738471490","https://openalex.org/W6740005241","https://openalex.org/W6751647823","https://openalex.org/W6756561102","https://openalex.org/W6758632346","https://openalex.org/W6762174034","https://openalex.org/W6771630921","https://openalex.org/W6780489652","https://openalex.org/W6803865595"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W4221142204"],"abstract_inverted_index":{"Graph":[0],"neural":[1],"networks":[2],"(GNNs)":[3],"have":[4],"achieved":[5],"promising":[6],"results":[7],"for":[8,50,91],"node":[9,113],"classification":[10],"tasks.":[11],"However,":[12],"due":[13],"to":[14,38,60,82],"the":[15,22,62,73,110],"memorization":[16],"effects,":[17],"GNNs":[18,65,77],"easily":[19],"overfit":[20],"in":[21],"presence":[23],"of":[24,64,112,124],"label":[25,97],"noise.":[26],"Currently,":[27],"this":[28,33,40],"problem":[29],"remains":[30],"open.":[31],"In":[32],"paper,":[34],"we":[35],"propose":[36],"CLaSS":[37,55,94,125],"bridge":[39],"important":[41],"gap.":[42],"It":[43],"is":[44],"a":[45],"first-of-its-kind":[46],"sample":[47],"selection-based":[48],"framework":[49],"training":[51],"noise-resistant":[52],"GNNs.":[53],"Specifically,":[54],"performs":[56,96],"graph":[57],"contrastive":[58],"learning":[59],"improve":[61],"robustness":[63],"and":[66,86,103],"effectively":[67],"leverages":[68],"unlabeled":[69],"nodes.":[70],"To":[71],"mitigate":[72],"confirmation":[74],"bias,":[75],"two":[76],"are":[78],"trained":[79],"through":[80],"co-teaching":[81],"select":[83],"true-labeled":[84],"nodes":[85,90,102],"filter":[87],"out":[88],"noisy":[89,107],"each":[92],"other.":[93],"also":[95],"refinement":[98],"on":[99,105,117],"selected":[100,106],"clean":[101],"guessing":[104],"ones,":[108],"with":[109],"help":[111],"clustering.":[114],"Extensive":[115],"experiments":[116],"four":[118],"real-world":[119],"datasets":[120],"demonstrate":[121],"significant":[122],"advantages":[123],"over":[126],"five":[127],"state-of-the-art":[128],"approaches.":[129]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}