{"id":"https://openalex.org/W2114054107","doi":"https://doi.org/10.1109/ijcnn.2008.4634054","title":"Reduction of difference among trained neural networks by re-learning","display_name":"Reduction of difference among trained neural networks by re-learning","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2114054107","doi":"https://doi.org/10.1109/ijcnn.2008.4634054","mag":"2114054107"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2008.4634054","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634054","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","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/A5100724297","display_name":"Yong Liu","orcid":"https://orcid.org/0000-0003-4822-8939"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yong Liu","raw_affiliation_strings":["Department of Computer Hardware, University of Aizu, Fukushima, Japan","Dept. of Comput. Hardware, Univ. of Aizu, Aizuwakamatsu"],"affiliations":[{"raw_affiliation_string":"Department of Computer Hardware, University of Aizu, Fukushima, Japan","institution_ids":["https://openalex.org/I141591182"]},{"raw_affiliation_string":"Dept. of Comput. Hardware, Univ. of Aizu, Aizuwakamatsu","institution_ids":["https://openalex.org/I141591182"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100724297"],"corresponding_institution_ids":["https://openalex.org/I141591182"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09421503,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1880","last_page":"1884"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9994999766349792,"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/T10320","display_name":"Neural Networks and Applications","score":0.9994999766349792,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9781000018119812,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/artificial-neural-network","display_name":"Artificial neural network","score":0.798724889755249},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7186240553855896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6661677360534668},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6238048672676086},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4730357825756073},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.46323487162590027},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.44114816188812256},{"id":"https://openalex.org/keywords/types-of-artificial-neural-networks","display_name":"Types of artificial neural networks","score":0.4345184862613678},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.31861600279808044},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12366381287574768}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.798724889755249},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7186240553855896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6661677360534668},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6238048672676086},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4730357825756073},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.46323487162590027},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.44114816188812256},{"id":"https://openalex.org/C177973122","wikidata":"https://www.wikidata.org/wiki/Q7860946","display_name":"Types of artificial neural networks","level":4,"score":0.4345184862613678},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.31861600279808044},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12366381287574768},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2008.4634054","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634054","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1967646346","https://openalex.org/W2116374865","https://openalex.org/W2134514463","https://openalex.org/W2135293965","https://openalex.org/W2144801536","https://openalex.org/W2766736793","https://openalex.org/W6681465115","https://openalex.org/W6682610290"],"related_works":["https://openalex.org/W1584270863","https://openalex.org/W2149978162","https://openalex.org/W2083677758","https://openalex.org/W2950022897","https://openalex.org/W1973323485","https://openalex.org/W2373874059","https://openalex.org/W2109916967","https://openalex.org/W3109717595","https://openalex.org/W4390190477","https://openalex.org/W1595652908"],"abstract_inverted_index":{"It":[0],"is":[1],"often":[2],"that":[3],"the":[4,14],"learned":[5,57],"neural":[6,32,58],"networks":[7,59],"end":[8],"with":[9,72],"different":[10,46],"decision":[11],"boundaries":[12],"under":[13],"variations":[15,27],"of":[16],"training":[17],"data,":[18],"learning":[19],"algorithms,":[20],"architectures,":[21],"and":[22,88],"initial":[23],"random":[24],"weights.":[25],"Such":[26],"are":[28,36],"helpful":[29],"in":[30],"designing":[31],"network":[33],"ensembles,":[34],"but":[35],"harmful":[37],"for":[38,56],"making":[39],"unstable":[40],"performances,":[41],"i.e.,":[42],"large":[43],"variances":[44,55],"among":[45],"learnings.":[47],"This":[48],"paper":[49],"discusses":[50],"how":[51,87],"to":[52,85],"reduce":[53],"such":[54,90],"by":[60],"letting":[61],"them":[62],"re-learn":[63],"on":[64,68,80],"those":[65],"data":[66],"points":[67],"which":[69],"they":[70],"disagrees":[71],"each":[73],"other.":[74],"Experimental":[75],"results":[76],"have":[77],"been":[78],"conducted":[79],"four":[81],"real":[82],"world":[83],"applications":[84],"explain":[86],"when":[89],"re-learning":[91],"works.":[92]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
