{"id":"https://openalex.org/W7123363342","doi":"https://doi.org/10.1109/cdc57313.2025.11312827","title":"A Naive Aggregation Algorithm for Improving Generalization in a Class of Learning Problems","display_name":"A Naive Aggregation Algorithm for Improving Generalization in a Class of Learning Problems","publication_year":2025,"publication_date":"2025-12-09","ids":{"openalex":"https://openalex.org/W7123363342","doi":"https://doi.org/10.1109/cdc57313.2025.11312827"},"language":null,"primary_location":{"id":"doi:10.1109/cdc57313.2025.11312827","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc57313.2025.11312827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 64th Conference on Decision and Control (CDC)","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/A5005744799","display_name":"Getachew K. Befekadu","orcid":"https://orcid.org/0000-0001-5846-4201"},"institutions":[{"id":"https://openalex.org/I168959743","display_name":"University of America","ror":"https://ror.org/03s0c9350","country_code":"US","type":"education","lineage":["https://openalex.org/I168959743"]},{"id":"https://openalex.org/I84470341","display_name":"Catholic University of America","ror":"https://ror.org/047yk3s18","country_code":"US","type":"education","lineage":["https://openalex.org/I84470341"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Getachew K. Befekadu","raw_affiliation_strings":["The Catholic University of America,School of Engineering,Department of Electrical and Computer Engineering,Washington, DC,USA,20064"],"affiliations":[{"raw_affiliation_string":"The Catholic University of America,School of Engineering,Department of Electrical and Computer Engineering,Washington, DC,USA,20064","institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5005744799"],"corresponding_institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.82382175,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6134","last_page":"6137"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.1687999963760376,"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":0.1687999963760376,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.10109999775886536,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.0794999971985817,"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/generalization","display_name":"Generalization","score":0.701200008392334},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5609999895095825},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4819999933242798},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47690001130104065},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.44449999928474426},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4408000111579895},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4296000003814697},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41119998693466187},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.387800008058548}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.701200008392334},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5609999895095825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5134999752044678},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48750001192092896},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48669999837875366},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4819999933242798},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48030000925064087},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47690001130104065},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.44449999928474426},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4408000111579895},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43459999561309814},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4296000003814697},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41119998693466187},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.387800008058548},{"id":"https://openalex.org/C117765406","wikidata":"https://www.wikidata.org/wiki/Q5362437","display_name":"Generalization error","level":3,"score":0.3749000132083893},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37380000948905945},{"id":"https://openalex.org/C176248197","wikidata":"https://www.wikidata.org/wiki/Q458526","display_name":"Probably approximately correct learning","level":4,"score":0.33869999647140503},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.3077000081539154},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C24138899","wikidata":"https://www.wikidata.org/wiki/Q17141258","display_name":"Instance-based learning","level":3,"score":0.2718999981880188},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C50292564","wikidata":"https://www.wikidata.org/wiki/Q2462783","display_name":"Computational learning theory","level":3,"score":0.2599000036716461},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.2578999996185303},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C95627357","wikidata":"https://www.wikidata.org/wiki/Q7979889","display_name":"Weighted Majority Algorithm","level":5,"score":0.2513999938964844},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cdc57313.2025.11312827","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc57313.2025.11312827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 64th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7279106378555298}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,40],"this":[1,153],"brief":[2],"paper,":[3],"we":[4,42,155],"present":[5,156],"a":[6,11,36,44,58,105,127,161],"naive":[7],"aggregation":[8],"algorithm":[9,101],"for":[10,52,112,130,160],"typical":[12,162],"learning":[13,33,47,147],"problem":[14,48],"with":[15,73],"expert":[16],"advice":[17],"setting,":[18],"in":[19,31,141],"which":[20,98,133],"the":[21,32,67,80,86,114],"task":[22],"of":[23,46,49,60,70,107,143,152,164],"improving":[24],"generalization,":[25],"i.e.,":[26,125],"model":[27],"validation,":[28],"is":[29,93,134],"embedded":[30],"process":[34],"as":[35,126,150],"sequential":[37],"decision-making":[38],"problem.":[39,167],"particular,":[41],"consider":[43],"class":[45],"point":[50],"estimations":[51],"modeling":[53],"high-dimensional":[54],"nonlinear":[55,165],"functions,":[56],"where":[57],"group":[59],"experts":[61],"update":[62],"their":[63],"parameter":[64,123],"estimates":[65,116],"using":[66],"discrete-time":[68],"version":[69],"gradient":[71],"systems,":[72],"small":[74],"additive":[75],"noise":[76],"term,":[77],"guided":[78],"by":[79],"corresponding":[81],"subsample":[82],"datasets":[83],"obtained":[84],"from":[85],"original":[87],"dataset.":[88],"Here,":[89],"our":[90],"main":[91],"objective":[92],"to":[94,120],"provide":[95],"conditions":[96],"under":[97],"such":[99],"an":[100,121],"will":[102],"sequentially":[103],"determine":[104],"set":[106],"mixing":[108],"distribution":[109],"strategies":[110],"used":[111],"aggregating":[113],"experts\u2019":[115],"that":[117],"ultimately":[118],"leading":[119],"optimal":[122],"estimate,":[124],"consensus":[128],"solution":[129],"all":[131],"experts,":[132],"better":[135],"than":[136],"any":[137],"individual":[138],"expert\u2019s":[139],"estimate":[140],"terms":[142],"improved":[144],"generalization":[145],"or":[146],"performances.":[148],"Finally,":[149],"part":[151],"work,":[154],"some":[157],"numerical":[158],"results":[159],"case":[163],"regression":[166]},"counts_by_year":[],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2026-01-14T00:00:00"}