{"id":"https://openalex.org/W3023257565","doi":"https://doi.org/10.1587/transinf.2019edp7177","title":"Neural Behavior-Based Approach for Neural Network Pruning","display_name":"Neural Behavior-Based Approach for Neural Network Pruning","publication_year":2020,"publication_date":"2020-04-30","ids":{"openalex":"https://openalex.org/W3023257565","doi":"https://doi.org/10.1587/transinf.2019edp7177","mag":"3023257565"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2019edp7177","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2019edp7177","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E103.D/5/E103.D_2019EDP7177/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/E103.D/5/E103.D_2019EDP7177/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014087776","display_name":"Koji KAMMA","orcid":null},"institutions":[{"id":"https://openalex.org/I75198481","display_name":"Wakayama University","ror":"https://ror.org/05wr49d48","country_code":"JP","type":"education","lineage":["https://openalex.org/I75198481"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Koji KAMMA","raw_affiliation_strings":["Wakayama University"],"affiliations":[{"raw_affiliation_string":"Wakayama University","institution_ids":["https://openalex.org/I75198481"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077704289","display_name":"Yuki Isoda","orcid":null},"institutions":[{"id":"https://openalex.org/I75198481","display_name":"Wakayama University","ror":"https://ror.org/05wr49d48","country_code":"JP","type":"education","lineage":["https://openalex.org/I75198481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuki ISODA","raw_affiliation_strings":["Wakayama University"],"affiliations":[{"raw_affiliation_string":"Wakayama University","institution_ids":["https://openalex.org/I75198481"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083467669","display_name":"Sarimu INOUE","orcid":null},"institutions":[{"id":"https://openalex.org/I75198481","display_name":"Wakayama University","ror":"https://ror.org/05wr49d48","country_code":"JP","type":"education","lineage":["https://openalex.org/I75198481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sarimu INOUE","raw_affiliation_strings":["Wakayama University"],"affiliations":[{"raw_affiliation_string":"Wakayama University","institution_ids":["https://openalex.org/I75198481"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112614625","display_name":"Toshikazu Wada","orcid":null},"institutions":[{"id":"https://openalex.org/I75198481","display_name":"Wakayama University","ror":"https://ror.org/05wr49d48","country_code":"JP","type":"education","lineage":["https://openalex.org/I75198481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toshikazu WADA","raw_affiliation_strings":["Wakayama University"],"affiliations":[{"raw_affiliation_string":"Wakayama University","institution_ids":["https://openalex.org/I75198481"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014087776"],"corresponding_institution_ids":["https://openalex.org/I75198481"],"apc_list":null,"apc_paid":null,"fwci":0.3977,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67547007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"E103.D","issue":"5","first_page":"1135","last_page":"1143"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9976000189781189,"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":0.9976000189781189,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9975000023841858,"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":0.995199978351593,"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":0.9024257659912109},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7919623851776123},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7371339797973633},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5904056429862976},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4641401171684265},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.4476293623447418},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4314875602722168}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9024257659912109},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7919623851776123},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7371339797973633},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5904056429862976},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4641401171684265},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.4476293623447418},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4314875602722168},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2019edp7177","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2019edp7177","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E103.D/5/E103.D_2019EDP7177/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2019edp7177","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2019edp7177","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E103.D/5/E103.D_2019EDP7177/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3023257565.pdf","grobid_xml":"https://content.openalex.org/works/W3023257565.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W992687842","https://openalex.org/W1667652561","https://openalex.org/W1845051632","https://openalex.org/W1902934009","https://openalex.org/W1935978687","https://openalex.org/W2084910356","https://openalex.org/W2108598243","https://openalex.org/W2114766824","https://openalex.org/W2156150815","https://openalex.org/W2194775991","https://openalex.org/W2294543795","https://openalex.org/W2515385951","https://openalex.org/W2707890836","https://openalex.org/W2739879705","https://openalex.org/W2751438535","https://openalex.org/W2899771611","https://openalex.org/W2962835968","https://openalex.org/W2964217848","https://openalex.org/W2964233199","https://openalex.org/W2964299589"],"related_works":["https://openalex.org/W2386387936","https://openalex.org/W1629725936","https://openalex.org/W3199608561","https://openalex.org/W1540849649","https://openalex.org/W2187121994","https://openalex.org/W2171621711","https://openalex.org/W2367207292","https://openalex.org/W4206024927","https://openalex.org/W2802349271","https://openalex.org/W3200578280"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,39],"method":[4,24,72,87,102,154],"for":[5,106],"reducing":[6],"the":[7,33,54,57,67,70,74,78,81,85,90,113,116,143,152,158],"redundancy":[8],"in":[9],"both":[10],"fully":[11],"connected":[12],"layers":[13,16,109],"and":[14,49,128,141],"convolutional":[15,108,114],"of":[17,26,35,42,62,66,80,92,97,118],"trained":[18],"neural":[19],"network":[20],"models.":[21],"The":[22],"proposed":[23,71,86,153],"consists":[25],"two":[27],"steps,":[28],"1)":[29],"Neuro-Coding:":[30],"to":[31,46,52],"encode":[32],"behavior":[34,79,117],"each":[36,119],"neuron":[37,76],"by":[38,123,136],"vector":[40],"composed":[41],"its":[43,124],"outputs":[44],"corresponding":[45],"actual":[47],"inputs":[48],"2)":[50],"Neuro-Unification:":[51],"unify":[53],"neurons":[55,93],"having":[56],"similar":[58,68],"behavioral":[59],"vectors.":[60],"Instead":[61],"just":[63],"pruning":[64],"one":[65],"neurons,":[69],"let":[73],"remaining":[75,144],"emulate":[77],"pruned":[82,140],"one.":[83],"Therefore,":[84],"can":[88,103,132],"reduce":[89],"number":[91],"with":[94],"small":[95],"sacrifice":[96],"accuracy":[98],"without":[99],"retraining.":[100],"Our":[101],"be":[104,133],"applied":[105],"compressing":[107],"as":[110],"well.":[111],"In":[112],"layers,":[115],"channel":[120],"is":[121],"encoded":[122],"output":[125],"feature":[126],"maps,":[127],"channels":[129,138],"whose":[130],"behaviors":[131],"well":[134],"emulated":[135],"other":[137],"are":[139],"update":[142],"weights.":[145],"Through":[146],"several":[147],"experiments,":[148],"we":[149],"comfirmed":[150],"that":[151],"performs":[155],"better":[156],"than":[157],"existing":[159],"methods.":[160]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"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"}