{"id":"https://openalex.org/W4416251460","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229180","title":"Enhancing Branching Policy Generalization through Self-Supervised Adversarial Instance Augmentation","display_name":"Enhancing Branching Policy Generalization through Self-Supervised Adversarial Instance Augmentation","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251460","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229180"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11229180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229180","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5004750246","display_name":"Ce Zhang","orcid":"https://orcid.org/0000-0001-5100-3584"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ce Zhang","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Automation"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Automation","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100392889","display_name":"Bin Zhang","orcid":"https://orcid.org/0000-0003-0304-2372"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Zhang","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Automation"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Automation","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009920838","display_name":"Xiaoshu L\u00fc","orcid":"https://orcid.org/0000-0002-1928-8580"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyue Lu","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Automation"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Automation","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016996180","display_name":"Guoliang Fan","orcid":"https://orcid.org/0000-0002-8584-9040"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoliang Fan","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Automation"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Automation","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5004750246"],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1947199,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.18610000610351562,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.18610000610351562,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.18549999594688416,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.08659999817609787,"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/adversarial-system","display_name":"Adversarial system","score":0.808899998664856},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7271999716758728},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4593000113964081},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4530999958515167},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.447299987077713},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.3635999858379364},{"id":"https://openalex.org/keywords/branching","display_name":"Branching (polymer chemistry)","score":0.3517000079154968}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.808899998664856},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7271999716758728},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6635000109672546},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48579999804496765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48330000042915344},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4593000113964081},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4530999958515167},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.447299987077713},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3635999858379364},{"id":"https://openalex.org/C206175624","wikidata":"https://www.wikidata.org/wiki/Q595731","display_name":"Branching (polymer chemistry)","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.3334999978542328},{"id":"https://openalex.org/C117765406","wikidata":"https://www.wikidata.org/wiki/Q5362437","display_name":"Generalization error","level":3,"score":0.33180001378059387},{"id":"https://openalex.org/C5465570","wikidata":"https://www.wikidata.org/wiki/Q5326898","display_name":"Early stopping","level":3,"score":0.30640000104904175},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2924000024795532},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2678000032901764},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11229180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229180","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2091364465","https://openalex.org/W2108648237","https://openalex.org/W2171074980","https://openalex.org/W2951360122","https://openalex.org/W2998442330","https://openalex.org/W3173319990","https://openalex.org/W3204908603","https://openalex.org/W4283797864","https://openalex.org/W4321634665","https://openalex.org/W4401813859"],"related_works":[],"abstract_inverted_index":{"Mixed-Integer":[0],"Linear":[1],"Programming":[2],"(MILP)":[3],"has":[4,61],"extensive":[5],"applications":[6],"in":[7,80,154],"real-world":[8],"scenarios,":[9],"with":[10],"the":[11,16,41,46,51,69,77,135,156],"Branch-and-Bound":[12],"(B&B)":[13],"algorithm":[14],"being":[15],"most":[17],"commonly":[18],"utilized":[19],"method":[20,82],"for":[21,75],"its":[22],"resolution.":[23],"Recently,":[24],"an":[25],"increasing":[26],"number":[27],"of":[28,71,137,158],"studies":[29],"have":[30],"investigated":[31],"learning-based":[32,100],"approaches":[33],"aimed":[34],"at":[35],"replacing":[36],"heuristic":[37],"branching":[38],"rules":[39],"within":[40],"B&B":[42],"framework":[43],"to":[44,64,85,114,125],"expedite":[45],"solving":[47],"process.":[48],"To":[49,89],"mitigate":[50],"generalization":[52,142,157],"challenges":[53],"encountered":[54],"by":[55],"these":[56],"methods,":[57],"Adversarial":[58,101],"Instance":[59],"Augmentation":[60,103],"been":[62],"proposed":[63],"generate":[65],"diverse":[66,130],"instances.":[67],"However,":[68],"application":[70],"reinforcement":[72],"learning":[73,113,124],"(RL)":[74],"training":[76],"instance":[78,131],"generator":[79],"this":[81,91],"significantly":[83],"leads":[84],"low":[86],"data":[87,167],"efficiency.":[88,168],"address":[90],"issue,":[92],"we":[93],"introduce":[94],"a":[95,128],"novel":[96],"approach":[97],"termed":[98],"Self-supervised":[99],"insTance":[102],"(SATA).":[104],"Rather":[105],"than":[106],"relying":[107],"on":[108],"RL,":[109],"SATA":[110,148],"utilizes":[111],"self-supervised":[112],"develop":[115],"effective":[116],"masking":[117],"capabilities.":[118],"Additionally,":[119],"it":[120],"employs":[121],"adversarial":[122],"augmentation":[123],"efficiently":[126],"train":[127],"more":[129],"generator,":[132],"thereby":[133],"overcoming":[134],"issue":[136],"sample":[138],"efficiency":[139],"while":[140],"maintaining":[141],"performance.":[143],"Experimental":[144],"results":[145],"demonstrate":[146],"that":[147],"not":[149],"only":[150],"surpasses":[151],"all":[152],"baselines":[153],"improving":[155],"Branching":[159],"Variable":[160],"Selection":[161],"policy":[162],"but":[163],"also":[164],"achieves":[165],"superior":[166]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}
