{"id":"https://openalex.org/W4297838890","doi":"https://doi.org/10.14428/esann/2022.es2022-99","title":"Biased Edge Dropout in NIFTY for Fair Graph Representation Learning","display_name":"Biased Edge Dropout in NIFTY for Fair Graph Representation Learning","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4297838890","doi":"https://doi.org/10.14428/esann/2022.es2022-99"},"language":"en","primary_location":{"id":"doi:10.14428/esann/2022.es2022-99","is_oa":true,"landing_page_url":"http://doi.org/10.14428/esann/2022.es2022-99","pdf_url":"https://doi.org/10.14428/esann/2022.es2022-99","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2022 proceedings","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.14428/esann/2022.es2022-99","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032939859","display_name":"Federico Caldart","orcid":"https://orcid.org/0000-0002-2798-552X"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Federico Caldart","raw_affiliation_strings":["-University of Padua, Via Trieste 63, 35121, Padua, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"-University of Padua, Via Trieste 63, 35121, Padua, Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065003610","display_name":"Luca Pasa","orcid":"https://orcid.org/0000-0002-3023-3046"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Pasa","raw_affiliation_strings":["-University of Padua, Via Trieste 63, 35121, Padua, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"-University of Padua, Via Trieste 63, 35121, Padua, Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045802198","display_name":"Luca Oneto","orcid":"https://orcid.org/0000-0002-8445-395X"},"institutions":[{"id":"https://openalex.org/I83816512","display_name":"University of Genoa","ror":"https://ror.org/0107c5v14","country_code":"IT","type":"education","lineage":["https://openalex.org/I83816512"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Oneto","raw_affiliation_strings":["-University of Genoa, Via Opera Pia 11a, 16145, Genova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"-University of Genoa, Via Opera Pia 11a, 16145, Genova, Italy","institution_ids":["https://openalex.org/I83816512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064873591","display_name":"Alessandro Sperduti","orcid":"https://orcid.org/0000-0002-8686-850X"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessandro Sperduti","raw_affiliation_strings":["-University of Padua, Via Trieste 63, 35121, Padua, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"-University of Padua, Via Trieste 63, 35121, Padua, Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088959189","display_name":"Nicol\u00f2 Navarin","orcid":"https://orcid.org/0000-0002-4108-1754"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nicol\u00f2 Navarin","raw_affiliation_strings":["-University of Padua, Via Trieste 63, 35121, Padua, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"-University of Padua, Via Trieste 63, 35121, Padua, Italy","institution_ids":["https://openalex.org/I138689650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1387,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55331474,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"497","last_page":"502"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9850999712944031,"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":0.9850999712944031,"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/dropout","display_name":"Dropout (neural networks)","score":0.7321538925170898},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6673390865325928},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5993770360946655},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.565478503704071},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.522956907749176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4372323155403137},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3137816786766052},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2948931157588959}],"concepts":[{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.7321538925170898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6673390865325928},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5993770360946655},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.565478503704071},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.522956907749176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4372323155403137},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3137816786766052},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2948931157588959},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14428/esann/2022.es2022-99","is_oa":true,"landing_page_url":"http://doi.org/10.14428/esann/2022.es2022-99","pdf_url":"https://doi.org/10.14428/esann/2022.es2022-99","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2022 proceedings","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.14428/esann/2022.es2022-99","is_oa":true,"landing_page_url":"http://doi.org/10.14428/esann/2022.es2022-99","pdf_url":"https://doi.org/10.14428/esann/2022.es2022-99","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2022 proceedings","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4297838890.pdf","grobid_xml":"https://content.openalex.org/works/W4297838890.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W2116341502","https://openalex.org/W2139906443","https://openalex.org/W2166681504","https://openalex.org/W2519887557","https://openalex.org/W2530395818","https://openalex.org/W2804302783","https://openalex.org/W2945903605","https://openalex.org/W2964015378","https://openalex.org/W2996268457","https://openalex.org/W3006944694","https://openalex.org/W3012821910","https://openalex.org/W3082642400","https://openalex.org/W3097736165","https://openalex.org/W3132822009","https://openalex.org/W3133595540","https://openalex.org/W3186927324","https://openalex.org/W3192448376","https://openalex.org/W4206323856","https://openalex.org/W4287323365","https://openalex.org/W6677316912","https://openalex.org/W6728551298","https://openalex.org/W6751342375"],"related_works":["https://openalex.org/W3107474891","https://openalex.org/W1549289070","https://openalex.org/W4368274933","https://openalex.org/W1889934247","https://openalex.org/W3013056451","https://openalex.org/W2749920319","https://openalex.org/W3202678255","https://openalex.org/W4327572199","https://openalex.org/W3156809321","https://openalex.org/W1826416243"],"abstract_inverted_index":{"Graph":[0],"Neural":[1],"Networks":[2],"(GNNs)":[3],"are":[4],"nowadays":[5],"widely":[6],"used":[7],"in":[8,53,97],"many":[9],"real-world":[10,99],"applications.":[11],"Nonetheless,":[12],"the":[13,54,60,65,68,78,82,87,92],"data":[14,62],"relationships":[15],"can":[16],"be":[17],"a":[18,74],"source":[19],"of":[20,67,77,81,94],"biases":[21],"based":[22,57],"on":[23,58],"sensitive":[24],"attributes":[25],"(e.g.,":[26],"gender":[27],"or":[28],"ethnicity).":[29],"Several":[30],"methods":[31],"have":[32],"been":[33],"proposed":[34],"to":[35,63,85],"learn":[36],"fair":[37],"graph":[38,83,100],"node":[39],"representations.":[40],"In":[41,70],"this":[42],"work":[43],"we":[44,72],"extend":[45],"NIFTY,":[46],"an":[47],"approach":[48,96],"that":[49],"exploits":[50],"additional":[51],"terms":[52],"loss":[55],"function":[56],"perturbing":[59],"input":[61],"enforce":[64],"fairness":[66],"GNNs.":[69],"particular,":[71],"exploit":[73],"biased":[75],"perturbation":[76],"adjacency":[79],"matrix":[80],"able":[84],"reduce":[86],"edge":[88],"homophily.":[89],"We":[90],"show":[91],"effectiveness":[93],"our":[95],"four":[98],"datasets.":[101]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}