{"id":"https://openalex.org/W2552911551","doi":"https://doi.org/10.1109/mlsp.2016.7738869","title":"Memory reduction method for deep neural network training","display_name":"Memory reduction method for deep neural network training","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2552911551","doi":"https://doi.org/10.1109/mlsp.2016.7738869","mag":"2552911551"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2016.7738869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5102314855","display_name":"Koichi Shirahata","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koichi Shirahata","raw_affiliation_strings":["FUJITSU LABORATORIES LTD., Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FUJITSU LABORATORIES LTD., Kanagawa, Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102106206","display_name":"Yasumoto Tomita","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasumoto Tomita","raw_affiliation_strings":["FUJITSU LABORATORIES LTD., Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FUJITSU LABORATORIES LTD., Kanagawa, Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006634908","display_name":"Atsushi Ike","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsushi Ike","raw_affiliation_strings":["FUJITSU LABORATORIES LTD., Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FUJITSU LABORATORIES LTD., Kanagawa, Japan","institution_ids":["https://openalex.org/I2252096349"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1831,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.85814903,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","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"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7321630716323853},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.6380079984664917},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6126484870910645},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5720122456550598},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47730696201324463},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07402095198631287}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7321630716323853},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.6380079984664917},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6126484870910645},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5720122456550598},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47730696201324463},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07402095198631287},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp.2016.7738869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1667072054","https://openalex.org/W1667652561","https://openalex.org/W1686810756","https://openalex.org/W1724438581","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2132211083","https://openalex.org/W2146502635","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2272300165","https://openalex.org/W2964299589","https://openalex.org/W4302296459","https://openalex.org/W6637151318","https://openalex.org/W6637187546","https://openalex.org/W6637373629","https://openalex.org/W6637709462","https://openalex.org/W6681435938","https://openalex.org/W6684191040","https://openalex.org/W6687483927","https://openalex.org/W6693859313"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W230091440","https://openalex.org/W2390279801","https://openalex.org/W2233261550","https://openalex.org/W2358668433","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2997094352"],"abstract_inverted_index":{"Training":[0],"deep":[1,12,40],"neural":[2,13,41],"networks":[3,14],"requires":[4],"a":[5,29,39],"large":[6],"amount":[7,34],"of":[8,35],"memory,":[9],"making":[10],"very":[11],"difficult":[15],"to":[16,23,31,46,97],"fit":[17],"on":[18,78],"accelerator":[19],"memories.":[20],"In":[21],"order":[22],"overcome":[24],"this":[25],"limitation,":[26],"we":[27],"present":[28],"method":[30,44,68,85],"reduce":[32],"the":[33,51,56,61,70,92],"memory":[36,48,57,72],"for":[37,60],"training":[38,75,88],"network.":[42],"The":[43],"enables":[45],"suppress":[47],"increase":[49],"during":[50],"backward":[52],"pass,":[53],"by":[54,76,90],"reusing":[55],"regions":[58],"allocated":[59],"forward":[62],"pass.":[63],"Experimental":[64],"results":[65],"exhibit":[66],"our":[67],"reduced":[69],"occupied":[71],"size":[73,95],"in":[74],"44.7%":[77],"VGGNet":[79],"with":[80],"no":[81],"accuracy":[82],"affection.":[83],"Our":[84],"also":[86],"enabled":[87],"speedup":[89],"increasing":[91],"mini":[93],"batch":[94],"up":[96],"double.":[98]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
