{"id":"https://openalex.org/W4290948187","doi":"https://doi.org/10.1145/3534678.3539376","title":"Bilateral Dependency Optimization","display_name":"Bilateral Dependency Optimization","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4290948187","doi":"https://doi.org/10.1145/3534678.3539376"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539376","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539376","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2206.05483","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064514736","display_name":"Peng Xiong","orcid":"https://orcid.org/0000-0001-9866-4769"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Xiong Peng","raw_affiliation_strings":["Hong Kong Baptist University, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University, Hong Kong SAR, China","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100639398","display_name":"Feng Liu","orcid":"https://orcid.org/0000-0002-5005-9129"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Feng Liu","raw_affiliation_strings":["The University of Melbourne, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Melbourne, Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100749004","display_name":"Jingfeng Zhang","orcid":"https://orcid.org/0000-0003-3491-8074"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jingfeng Zhang","raw_affiliation_strings":["RIKEN AIP, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"RIKEN AIP, Tokyo, Japan","institution_ids":["https://openalex.org/I4210126580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060251766","display_name":"Long Lan","orcid":"https://orcid.org/0000-0002-4238-8985"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Long Lan","raw_affiliation_strings":["Hong Kong Baptist University, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University, Hong Kong SAR, China","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062108698","display_name":"Junjie Ye","orcid":"https://orcid.org/0000-0003-3924-008X"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Junjie Ye","raw_affiliation_strings":["The Hong Kong Polytechnic University, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University, Hong Kong SAR, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065250332","display_name":"Tongliang Liu","orcid":"https://orcid.org/0000-0002-9640-6472"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tongliang Liu","raw_affiliation_strings":["The University of Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047240103","display_name":"Bo Han","orcid":"https://orcid.org/0000-0002-6338-0958"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Bo Han","raw_affiliation_strings":["Hong Kong Baptist University, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University, Hong Kong SAR, China","institution_ids":["https://openalex.org/I141568987"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5064514736"],"corresponding_institution_ids":["https://openalex.org/I141568987"],"apc_list":null,"apc_paid":null,"fwci":1.9749,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.8854234,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1358","last_page":"1367"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","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/T11689","display_name":"Adversarial Robustness in Machine Learning","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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9950000047683716,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9731000065803528,"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/computer-science","display_name":"Computer science","score":0.7512673139572144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6073875427246094},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5714039206504822},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5335075855255127},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.48245149850845337},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4653528332710266},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42602983117103577},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3494740128517151}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7512673139572144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6073875427246094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5714039206504822},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5335075855255127},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.48245149850845337},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4653528332710266},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42602983117103577},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3494740128517151},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3534678.3539376","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539376","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2206.05483","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.05483","pdf_url":"https://arxiv.org/pdf/2206.05483","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2206.05483","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.05483","pdf_url":"https://arxiv.org/pdf/2206.05483","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1473189865","https://openalex.org/W1522301498","https://openalex.org/W1571599052","https://openalex.org/W1588424744","https://openalex.org/W1638081485","https://openalex.org/W1686810756","https://openalex.org/W1834627138","https://openalex.org/W2051267297","https://openalex.org/W2112796928","https://openalex.org/W2127658298","https://openalex.org/W2139710299","https://openalex.org/W2145287260","https://openalex.org/W2145544165","https://openalex.org/W2194775991","https://openalex.org/W2690721124","https://openalex.org/W2944954084","https://openalex.org/W2963684088","https://openalex.org/W2981828710","https://openalex.org/W3007508788","https://openalex.org/W3023716276","https://openalex.org/W3035574324","https://openalex.org/W3035616549","https://openalex.org/W3048684575","https://openalex.org/W3096738375","https://openalex.org/W3099206234","https://openalex.org/W3118608800","https://openalex.org/W3135588948","https://openalex.org/W3166872541","https://openalex.org/W3170901302","https://openalex.org/W3177170788","https://openalex.org/W3193581700","https://openalex.org/W3211698594","https://openalex.org/W3212332209","https://openalex.org/W3213758553","https://openalex.org/W4229820657","https://openalex.org/W4288567374","https://openalex.org/W4289761690","https://openalex.org/W4298201312","https://openalex.org/W4385245566","https://openalex.org/W6688325169"],"related_works":["https://openalex.org/W2067317451","https://openalex.org/W2154771632","https://openalex.org/W4211085505","https://openalex.org/W3122478268","https://openalex.org/W2084758217","https://openalex.org/W408804804","https://openalex.org/W4231021675","https://openalex.org/W3086365953","https://openalex.org/W4226072953","https://openalex.org/W2392606101"],"abstract_inverted_index":{"Through":[0],"using":[1,176],"only":[2],"a":[3,35,58,120,134,203,213,228],"well-trained":[4,220],"classifier,":[5,17],"model-inversion":[6],"(MI)":[7],"attacks":[8,86,210],"can":[9,151],"recover":[10],"the":[11,16,20,24,42,54,64,71,100,103,107,111,117,130,164,198,219],"data":[12],"used":[13,142],"for":[14,144,202],"training":[15,25,53],"leading":[18],"to":[19,69,98,140,159,218,231],"privacy":[21],"leakage":[22],"of":[23,166,173,205],"data.":[26],"To":[27,162],"defend":[28,232],"against":[29,84,233],"MI":[30,85,209,234],"attacks,":[31],"previous":[32],"work":[33],"utilizes":[34],"unilateral":[36],"dependency":[37,43,72,101,112,122,131,156,179],"optimization":[38,123],"strategy,":[39,168],"i.e.,":[40],"minimizing":[41,63],"between":[44,73,81,102,113],"inputs":[45,74,108],"(i.e.,":[46,50],"features)":[47],"and":[48,75,87,106,116,186,208],"outputs":[49],"labels)":[51],"during":[52],"classifier.":[55],"However,":[56],"such":[57],"minimization":[59],"process":[60],"conflicts":[61],"with":[62,154,182,188,222],"supervised":[65],"loss":[66],"that":[67,195],"aims":[68],"maximize":[70],"outputs,":[76,118],"causing":[77],"an":[78],"explicit":[79],"trade-off":[80],"model":[82,88],"robustness":[83],"utility":[89],"on":[90],"classification":[91],"tasks.":[92,161],"In":[93,126],"this":[94],"paper,":[95],"we":[96,128,169],"aim":[97],"minimize":[99],"latent":[104,114],"representations":[105,115],"while":[109,211],"maximizing":[110],"named":[119],"bilateral":[121],"(BiDO)":[124],"strategy.":[125],"particular,":[127],"use":[129],"constraints":[132],"as":[133],"universally":[135],"applicable":[136],"regularizer":[137],"in":[138],"addition":[139],"commonly":[141],"losses":[143],"deep":[145],"neural":[146],"networks":[147],"(e.g.,":[148],"cross-entropy),":[149],"which":[150,225],"be":[152],"instantiated":[153],"appropriate":[155],"criteria":[157],"according":[158],"different":[160,178],"verify":[163],"efficacy":[165],"our":[167],"propose":[170],"two":[171,177],"implementations":[172],"BiDO,":[174],"by":[175],"measures:":[180],"BiDO":[181,187,196],"constrained":[183],"covariance":[184],"(BiDO-COCO)":[185],"Hilbert-Schmidt":[189],"Independence":[190],"Criterion":[191],"(BiDO-HSIC).":[192],"Experiments":[193],"show":[194],"achieves":[197],"state-of-the-art":[199],"defense":[200],"performance":[201],"variety":[204],"datasets,":[206],"classifiers,":[207],"suffering":[212],"minor":[214],"classification-accuracy":[215],"drop":[216],"compared":[217],"classifier":[221],"no":[223],"defense,":[224],"lights":[226],"up":[227],"novel":[229],"road":[230],"attacks.":[235]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-08-13T00:00:00"}
