{"id":"https://openalex.org/W3171081089","doi":"https://doi.org/10.1109/ieeeconf51394.2020.9443551","title":"Distributed Boosting Classifiers over Noisy Channels","display_name":"Distributed Boosting Classifiers over Noisy Channels","publication_year":2020,"publication_date":"2020-11-01","ids":{"openalex":"https://openalex.org/W3171081089","doi":"https://doi.org/10.1109/ieeeconf51394.2020.9443551","mag":"3171081089"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf51394.2020.9443551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf51394.2020.9443551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","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/A5025186204","display_name":"Yongjune Kim","orcid":"https://orcid.org/0000-0003-0120-3750"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Yongjune Kim","raw_affiliation_strings":["DGIST, Daegu, South Korea"],"affiliations":[{"raw_affiliation_string":"DGIST, Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063057008","display_name":"Yuval Cassuto","orcid":"https://orcid.org/0000-0001-6369-6699"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yuval Cassuto","raw_affiliation_strings":["Technion \u2013 Israel Institute of Technology, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Technion \u2013 Israel Institute of Technology, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065423139","display_name":"Lav R. Varshney","orcid":"https://orcid.org/0000-0003-2798-5308"},"institutions":[{"id":"https://openalex.org/I4210155268","display_name":"Salesforce (United States)","ror":"https://ror.org/057315g56","country_code":"US","type":"company","lineage":["https://openalex.org/I4210155268"]},{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lav R. Varshney","raw_affiliation_strings":["Salesforce Research, Palo Alto, CA, USA","University of Illinois at Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"Salesforce Research, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I4210155268"]},{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025186204"],"corresponding_institution_ids":["https://openalex.org/I193352282"],"apc_list":null,"apc_paid":null,"fwci":0.6628,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77145215,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1491","last_page":"1496"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9991999864578247,"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":0.9991999864578247,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9988999962806702,"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":0.9968000054359436,"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/boosting","display_name":"Boosting (machine learning)","score":0.9645764827728271},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.787480354309082},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7129296660423279},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6849988698959351},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6513152122497559},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.616476833820343},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.5326933860778809},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3322516083717346},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.27017343044281006}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.9645764827728271},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.787480354309082},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7129296660423279},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6849988698959351},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6513152122497559},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.616476833820343},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.5326933860778809},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3322516083717346},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.27017343044281006}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieeeconf51394.2020.9443551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf51394.2020.9443551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1534477342","https://openalex.org/W1570592793","https://openalex.org/W1601795611","https://openalex.org/W1605688901","https://openalex.org/W1663973292","https://openalex.org/W1678356000","https://openalex.org/W1988790447","https://openalex.org/W2029218706","https://openalex.org/W2107189314","https://openalex.org/W2112076978","https://openalex.org/W2164598857","https://openalex.org/W2167460663","https://openalex.org/W2490901831","https://openalex.org/W2497735908","https://openalex.org/W2705659776","https://openalex.org/W2741318576","https://openalex.org/W2895367957","https://openalex.org/W2912934387","https://openalex.org/W2972471494","https://openalex.org/W3030378438","https://openalex.org/W3120740533","https://openalex.org/W3159649695","https://openalex.org/W3182208082","https://openalex.org/W4212883601","https://openalex.org/W4244259635","https://openalex.org/W6632075054","https://openalex.org/W6634164890","https://openalex.org/W6676769703","https://openalex.org/W6742116046","https://openalex.org/W6767960750","https://openalex.org/W6788247690"],"related_works":["https://openalex.org/W2327035729","https://openalex.org/W2348748958","https://openalex.org/W3039673966","https://openalex.org/W1538046993","https://openalex.org/W2884325279","https://openalex.org/W1570592793","https://openalex.org/W1525436954","https://openalex.org/W2385662756","https://openalex.org/W2585372724","https://openalex.org/W2241444561"],"abstract_inverted_index":{"We":[0,58,76,109],"present":[1],"a":[2,23,27],"principled":[3],"framework":[4],"to":[5,113],"address":[6],"resource":[7,78],"allocation":[8],"for":[9,71,86,103],"realizing":[10],"boosting":[11,95],"algorithms":[12],"on":[13],"substrates":[14],"with":[15],"communication":[16],"noise.":[17],"Boosting":[18],"classifiers":[19,36,96],"(e.g.,":[20],"AdaBoost)":[21],"make":[22],"final":[24,55],"decision":[25],"via":[26],"weighted":[28],"vote":[29],"from":[30],"local":[31],"decisions":[32],"of":[33,83,117],"many":[34],"base":[35,41,74],"(weak":[37],"classifiers).":[38],"Suppose":[39],"the":[40,54,92,115],"classifiers'":[42],"outputs":[43,51],"are":[44],"communicated":[45],"over":[46],"noisy":[47,50,94],"channels;":[48],"these":[49],"will":[52],"degrade":[53],"classification":[56],"accuracy.":[57],"show":[59,90],"this":[60],"degradation":[61],"can":[62,97],"be":[63,98],"effectively":[64],"reduced":[65],"by":[66],"allocating":[67],"more":[68,72,99],"system":[69],"resources":[70],"important":[73],"classifiers.":[75],"formulate":[77],"optimization":[79],"problems":[80],"in":[81],"terms":[82],"importance":[84],"metrics":[85],"boosting.":[87],"Moreover,":[88],"we":[89],"that":[91],"optimized":[93],"robust":[100],"than":[101],"bagging":[102],"noise":[104],"during":[105],"inference":[106],"(test":[107],"stage).":[108],"provide":[110],"numerical":[111],"evidence":[112],"demonstrate":[114],"benefits":[116],"our":[118],"approach.":[119]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
