{"id":"https://openalex.org/W2947527335","doi":"https://doi.org/10.1109/coolchips.2019.8721356","title":"Post Training Weight Compression with Distribution-based Filter-wise Quantization Step","display_name":"Post Training Weight Compression with Distribution-based Filter-wise Quantization Step","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2947527335","doi":"https://doi.org/10.1109/coolchips.2019.8721356","mag":"2947527335"},"language":"en","primary_location":{"id":"doi:10.1109/coolchips.2019.8721356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coolchips.2019.8721356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Symposium in Low-Power and High-Speed Chips (COOL CHIPS)","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/A5003908771","display_name":"Shin\u2010ichi Sasaki","orcid":"https://orcid.org/0000-0003-3676-6940"},"institutions":[{"id":"https://openalex.org/I1292669757","display_name":"Toshiba (Japan)","ror":"https://ror.org/0326v3z14","country_code":"JP","type":"company","lineage":["https://openalex.org/I1292669757"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shinichi Sasaki","raw_affiliation_strings":["Toshiba Memory Corporation, Institute of Memory Technology Research & Development"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toshiba Memory Corporation, Institute of Memory Technology Research & Development","institution_ids":["https://openalex.org/I1292669757"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039093381","display_name":"Asuka Maki","orcid":null},"institutions":[{"id":"https://openalex.org/I1292669757","display_name":"Toshiba (Japan)","ror":"https://ror.org/0326v3z14","country_code":"JP","type":"company","lineage":["https://openalex.org/I1292669757"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Asuka Maki","raw_affiliation_strings":["Toshiba Memory Corporation, Institute of Memory Technology Research & Development"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toshiba Memory Corporation, Institute of Memory Technology Research & Development","institution_ids":["https://openalex.org/I1292669757"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024598865","display_name":"Daisuke Miyashita","orcid":"https://orcid.org/0000-0003-2108-3397"},"institutions":[{"id":"https://openalex.org/I1292669757","display_name":"Toshiba (Japan)","ror":"https://ror.org/0326v3z14","country_code":"JP","type":"company","lineage":["https://openalex.org/I1292669757"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daisuke Miyashita","raw_affiliation_strings":["Toshiba Memory Corporation, Institute of Memory Technology Research & Development"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toshiba Memory Corporation, Institute of Memory Technology Research & Development","institution_ids":["https://openalex.org/I1292669757"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007360587","display_name":"Jun Deguchi","orcid":"https://orcid.org/0000-0002-3414-5537"},"institutions":[{"id":"https://openalex.org/I1292669757","display_name":"Toshiba (Japan)","ror":"https://ror.org/0326v3z14","country_code":"JP","type":"company","lineage":["https://openalex.org/I1292669757"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jun Deguchi","raw_affiliation_strings":["Toshiba Memory Corporation, Institute of Memory Technology Research & Development"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toshiba Memory Corporation, Institute of Memory Technology Research & Development","institution_ids":["https://openalex.org/I1292669757"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1292669757"],"apc_list":null,"apc_paid":null,"fwci":0.4063,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.6466272,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9984999895095825,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.8493769764900208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6895838975906372},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.652654230594635},{"id":"https://openalex.org/keywords/weight-distribution","display_name":"Weight distribution","score":0.5403701066970825},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.527150571346283},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.4968564808368683},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4894672632217407},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.48731598258018494},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47265851497650146},{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.4566989243030548},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.45343345403671265},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34583741426467896},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32002222537994385},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10163941979408264}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.8493769764900208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6895838975906372},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.652654230594635},{"id":"https://openalex.org/C25432639","wikidata":"https://www.wikidata.org/wiki/Q3711790","display_name":"Weight distribution","level":2,"score":0.5403701066970825},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.527150571346283},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.4968564808368683},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4894672632217407},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.48731598258018494},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47265851497650146},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.4566989243030548},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.45343345403671265},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34583741426467896},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32002222537994385},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10163941979408264},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/coolchips.2019.8721356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coolchips.2019.8721356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Symposium in Low-Power and High-Speed Chips (COOL CHIPS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W2172654076","https://openalex.org/W2194775991","https://openalex.org/W2776940252","https://openalex.org/W2809624076","https://openalex.org/W2907793133","https://openalex.org/W2912168260"],"related_works":["https://openalex.org/W2963318523","https://openalex.org/W2577708104","https://openalex.org/W2100968651","https://openalex.org/W4243803532","https://openalex.org/W1982606474","https://openalex.org/W2352648934","https://openalex.org/W4230688072","https://openalex.org/W1915693853","https://openalex.org/W2378212145","https://openalex.org/W2798892016"],"abstract_inverted_index":{"Quantization":[0],"of":[1,72],"models":[2],"with":[3,29,46,56,64],"lower":[4,22],"bit":[5,23],"precision":[6,62],"is":[7],"a":[8,43],"promising":[9],"method":[10],"to":[11,34],"develop":[12],"lower-power":[13],"and":[14,59],"smaller-area":[15],"neural":[16],"network":[17],"hardware.":[18],"However,":[19],"4-":[20],"or":[21],"quantization":[24,44,49],"usually":[25],"requires":[26],"additional":[27],"retraining":[28],"labeled":[30,52],"dataset":[31],"for":[32],"backpropagation":[33],"improve":[35],"test":[36],"accuracy.":[37],"In":[38],"this":[39],"paper,":[40],"we":[41],"propose":[42],"scheme":[45],"distribution-based":[47],"filter-wise":[48],"step":[50],"without":[51],"dataset.":[53],"ResNet-50":[54],"model":[55],"8-bit":[57],"activation":[58],"3.04-bit":[60],"weight":[61],"quantized":[63],"the":[65],"proposed":[66],"techniques":[67],"achieves":[68],"top-1":[69],"inference":[70],"accuracy":[71],"74.3%":[73],"on":[74],"ImageNet.":[75]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
