{"id":"https://openalex.org/W7124161114","doi":"https://doi.org/10.1109/icpads67057.2025.11323060","title":"Interpretable Bilevel Additive Taylor Model for Datasets with Noisy Labels and Imbalanced Classes","display_name":"Interpretable Bilevel Additive Taylor Model for Datasets with Noisy Labels and Imbalanced Classes","publication_year":2025,"publication_date":"2025-12-14","ids":{"openalex":"https://openalex.org/W7124161114","doi":"https://doi.org/10.1109/icpads67057.2025.11323060"},"language":null,"primary_location":{"id":"doi:10.1109/icpads67057.2025.11323060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11323060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","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/A5123025673","display_name":"Wenxing Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenxing Zhou","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University,Tianjin,China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123022570","display_name":"Chao Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Xu","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University,Tianjin,China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122993158","display_name":"Lian Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I164917862","display_name":"J-Power (Japan)","ror":"https://ror.org/04rbbpv92","country_code":"JP","type":"company","lineage":["https://openalex.org/I164917862"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Lian Peng","raw_affiliation_strings":["Hubei Central China Technology Development of Electric Power Co., Ltd,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"Hubei Central China Technology Development of Electric Power Co., Ltd,Wuhan,China","institution_ids":["https://openalex.org/I164917862"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100764999","display_name":"Xuelin Zhang","orcid":"https://orcid.org/0000-0003-1415-9402"},"institutions":[{"id":"https://openalex.org/I204823248","display_name":"Huazhong Agricultural University","ror":"https://ror.org/023b72294","country_code":"CN","type":"education","lineage":["https://openalex.org/I204823248"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuelin Zhang","raw_affiliation_strings":["College of Informatics, Huazhong Agricultural University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"College of Informatics, Huazhong Agricultural University,Wuhan,China","institution_ids":["https://openalex.org/I204823248"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5123025673"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.85941006,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.2313999980688095,"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":0.2313999980688095,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.18719999492168427,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.066600002348423,"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/interpretability","display_name":"Interpretability","score":0.9442999958992004},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.66839998960495},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5202000141143799},{"id":"https://openalex.org/keywords/bilevel-optimization","display_name":"Bilevel optimization","score":0.46540001034736633},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.39730000495910645},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.39239999651908875},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3847000002861023},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38260000944137573},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.3799000084400177}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9442999958992004},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6927000284194946},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.66839998960495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6013000011444092},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5781999826431274},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5202000141143799},{"id":"https://openalex.org/C3309286","wikidata":"https://www.wikidata.org/wiki/Q4907693","display_name":"Bilevel optimization","level":3,"score":0.46540001034736633},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39969998598098755},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.39730000495910645},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.39239999651908875},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3847000002861023},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3799000084400177},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3409000039100647},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.2847999930381775},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2782000005245209},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C137345334","wikidata":"https://www.wikidata.org/wiki/Q7303350","display_name":"Recursive partitioning","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.257099986076355},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C203223496","wikidata":"https://www.wikidata.org/wiki/Q4681344","display_name":"Additive model","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.2508000135421753},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpads67057.2025.11323060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11323060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.8067693710327148,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1998249287","https://openalex.org/W2024165284","https://openalex.org/W2142978414","https://openalex.org/W2593996946","https://openalex.org/W2787377517","https://openalex.org/W2795723870","https://openalex.org/W2805627121","https://openalex.org/W2899914520","https://openalex.org/W2945976633","https://openalex.org/W2963351448","https://openalex.org/W2979966119","https://openalex.org/W2999615587","https://openalex.org/W3004725381","https://openalex.org/W3005086430","https://openalex.org/W3015251297","https://openalex.org/W3034521057","https://openalex.org/W3043836048","https://openalex.org/W3094253649","https://openalex.org/W3120993127","https://openalex.org/W3137125108","https://openalex.org/W3171322015","https://openalex.org/W3196413773","https://openalex.org/W4238202755","https://openalex.org/W4244779605","https://openalex.org/W4300862723","https://openalex.org/W4312731594","https://openalex.org/W4367666062","https://openalex.org/W4379930608","https://openalex.org/W4381163198","https://openalex.org/W4382457792","https://openalex.org/W4382464384","https://openalex.org/W4384525165","https://openalex.org/W4384920712","https://openalex.org/W4386003349","https://openalex.org/W4390343577","https://openalex.org/W4399070662","https://openalex.org/W4400142106","https://openalex.org/W4402351755","https://openalex.org/W4403415522","https://openalex.org/W4406171589","https://openalex.org/W4407831865"],"related_works":[],"abstract_inverted_index":{"The":[0,96,175],"opacity":[1],"of":[2,98,150],"black-box":[3],"neural":[4,73],"networks":[5],"has":[6,181],"raised":[7],"significant":[8],"concerns":[9],"in":[10,105,135,164],"critical":[11],"domains":[12],"such":[13],"as":[14],"healthcare,":[15],"finance,":[16],"and":[17,22,44,64,86,113,138,162],"safety,":[18],"where":[19],"model":[20],"interpretability":[21,91,161],"robustness":[23,163],"are":[24],"essential":[25],"alongside":[26],"predictive":[27],"performance.":[28],"Existing":[29],"deep":[30],"learning":[31],"models":[32],"often":[33],"struggle":[34],"with":[35,71],"data":[36,118],"distribution":[37],"shifts,":[38],"including":[39],"label":[40,84],"noise,":[41],"class":[42,87],"imbalance,":[43],"outliers,":[45],"limiting":[46],"their":[47],"real-world":[48,126],"applicability.":[49],"To":[50],"address":[51],"these":[52],"challenges,":[53],"we":[54],"introduce":[55],"the":[56,106,147,158],"Bilevel":[57],"Additive":[58],"Taylor":[59,107],"Model":[60],"(BATM),":[61],"an":[62,78],"interpretable":[63],"robust":[65],"framework":[66],"that":[67,129],"integrates":[68],"bilevel":[69,152],"optimization":[70,153],"sparse":[72],"additive":[74,93],"modeling.":[75],"BATM":[76,130],"employs":[77],"adaptive":[79],"weighting":[80],"mechanism":[81],"to":[82,140],"mitigate":[83],"noise":[85],"imbalance":[88],"while":[89],"maintaining":[90],"through":[92],"feature":[94],"contributions.":[95],"incorporation":[97],"Tucker":[99],"decomposition":[100],"efficiently":[101],"handles":[102],"high-order":[103],"interactions":[104],"expansion,":[108],"substantially":[109],"reducing":[110],"computational":[111],"complexity":[112],"enhancing":[114],"scalability":[115],"for":[116,171,178],"large-scale":[117],"without":[119],"sacrificing":[120],"accuracy.":[121],"Extensive":[122],"experiments":[123],"on":[124],"multiple":[125],"datasets":[127],"demonstrate":[128],"outperforms":[131],"some":[132],"state-of-the-art":[133],"baselines":[134],"robustness,":[136],"interpretability,":[137],"resistance":[139],"catastrophic":[141],"forgetting.":[142],"Theoretical":[143],"analysis":[144],"further":[145],"guarantees":[146],"convergence":[148],"properties":[149],"our":[151],"scheme.":[154],"Our":[155],"work":[156],"bridges":[157],"gap":[159],"between":[160],"machine":[165],"learning,":[166],"offering":[167],"a":[168],"practical":[169],"solution":[170],"high-stakes":[172],"decision-making":[173],"scenarios.":[174],"implementation":[176],"code":[177],"this":[179],"research":[180],"been":[182],"made":[183],"publicly":[184],"available":[185],"at":[186],"https://github.com/tjuzwx/BATM.":[187]},"counts_by_year":[],"updated_date":"2026-01-16T23:16:36.188383","created_date":"2026-01-15T00:00:00"}