{"id":"https://openalex.org/W2149709822","doi":"https://doi.org/10.1109/icassp.2008.4517997","title":"A transductive extension of maximum entropy/iterative scaling for decision aggregation in distributed classification","display_name":"A transductive extension of maximum entropy/iterative scaling for decision aggregation in distributed classification","publication_year":2008,"publication_date":"2008-03-01","ids":{"openalex":"https://openalex.org/W2149709822","doi":"https://doi.org/10.1109/icassp.2008.4517997","mag":"2149709822"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2008.4517997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2008.4517997","pdf_url":null,"source":{"id":"https://openalex.org/S4210167542","display_name":"Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5074404271","display_name":"D.J. Miller","orcid":"https://orcid.org/0000-0002-5200-1457"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David J. Miller","raw_affiliation_strings":["Department of Electrical Engineering, Pennsylvania State University, University Park, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Pennsylvania State University, University Park, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101621515","display_name":"Yanxin Zhang","orcid":"https://orcid.org/0000-0002-1767-7371"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanxin Zhang","raw_affiliation_strings":["Department of Electrical Engineering, Pennsylvania State University, University Park, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Pennsylvania State University, University Park, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063903486","display_name":"George Kesidis","orcid":"https://orcid.org/0000-0001-7947-8127"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Kesidis","raw_affiliation_strings":["Department of Electrical Engineering, Pennsylvania State University, University Park, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Pennsylvania State University, University Park, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"1865","last_page":"1868"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9860000014305115,"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/computer-science","display_name":"Computer science","score":0.6746393442153931},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6630436778068542},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6230162978172302},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5677540302276611},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.47419291734695435},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.47108232975006104},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.46687716245651245},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.44193148612976074},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.41769614815711975},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35433533787727356},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.2980083227157593},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2278011441230774}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6746393442153931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6630436778068542},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6230162978172302},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5677540302276611},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.47419291734695435},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.47108232975006104},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.46687716245651245},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.44193148612976074},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.41769614815711975},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35433533787727356},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2980083227157593},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2278011441230774},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2008.4517997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2008.4517997","pdf_url":null,"source":{"id":"https://openalex.org/S4210167542","display_name":"Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7900000214576721,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2096175520","https://openalex.org/W2098835171","https://openalex.org/W2153381924","https://openalex.org/W3049188988"],"related_works":["https://openalex.org/W2394466068","https://openalex.org/W1987683558","https://openalex.org/W2726838704","https://openalex.org/W4220802396","https://openalex.org/W3041490575","https://openalex.org/W3024801493","https://openalex.org/W2913388591","https://openalex.org/W3007653948","https://openalex.org/W1957831838","https://openalex.org/W2970690932"],"abstract_inverted_index":{"Many":[0],"ensemble":[1],"classification":[2],"systems":[3],"apply":[4],"supervised":[5],"learning":[6,42,87],"to":[7,44,47,61,113],"design":[8],"a":[9,39,96,124],"function":[10],"for":[11,104],"combining":[12],"classifier":[13,23],"decisions,":[14],"which":[15],"requires":[16],"common":[17],"labeled":[18,52],"training":[19],"samples":[20,58],"across":[21],"the":[22,80,119],"ensemble.":[24],"Without":[25],"such":[26],"data,":[27],"fixed":[28],"rules":[29],"(voting,":[30],"Bayes":[31],"rule)":[32],"are":[33,70],"usually":[34],"applied.":[35,89],"[1]":[36],"alternatively":[37],"proposed":[38],"transductive":[40,97,121],"constraint-based":[41],"strategy":[43],"learn":[45],"how":[46],"fuse":[48],"decisions":[49,55],"even":[50],"without":[51],"examples.":[53],"There,":[54],"on":[56,123],"test":[57],"were":[59],"chosen":[60],"satisfy":[62],"constraints":[63,81],"measured":[64],"by":[65],"each":[66],"local":[67],"classifier.":[68],"There":[69],"two":[71],"main":[72],"limitations":[73],"of":[74,79,99,126],"that":[75],"work.":[76],"First,":[77],"feasibility":[78],"was":[82,88],"not":[83],"guaranteed.":[84],"Second,":[85],"heuristic":[86],"Here":[90],"we":[91],"overcome":[92],"both":[93],"problems":[94],"via":[95],"extension":[98],"maximum":[100],"entropy/improved":[101],"iterative":[102],"scaling":[103],"aggregation":[105],"in":[106],"distributed":[107],"classification.":[108],"This":[109],"method":[110],"is":[111],"shown":[112],"achieve":[114],"improved":[115],"decision":[116],"accuracy":[117],"over":[118],"earlier":[120],"approach":[122],"number":[125],"UC":[127],"Irvine":[128],"data":[129],"sets.":[130]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
