{"id":"https://openalex.org/W2580834719","doi":"https://doi.org/10.1109/bigcomp.2017.7881725","title":"CP-decomposition with Tensor Power Method for Convolutional Neural Networks compression","display_name":"CP-decomposition with Tensor Power Method for Convolutional Neural Networks compression","publication_year":2017,"publication_date":"2017-02-01","ids":{"openalex":"https://openalex.org/W2580834719","doi":"https://doi.org/10.1109/bigcomp.2017.7881725","mag":"2580834719"},"language":"en","primary_location":{"id":"doi:10.1109/bigcomp.2017.7881725","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigcomp.2017.7881725","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data and Smart Computing (BigComp)","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/A5042350375","display_name":"Marcella Astrid","orcid":"https://orcid.org/0000-0003-1432-6661"},"institutions":[{"id":"https://openalex.org/I88761825","display_name":"Korea University of Science and Technology","ror":"https://ror.org/000qzf213","country_code":"KR","type":"education","lineage":["https://openalex.org/I88761825"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Marcella Astrid","raw_affiliation_strings":["University of Science and Technology, Daejeon, South Korea","University of Science and Technology Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I88761825"]},{"raw_affiliation_string":"University of Science and Technology Daejeon, South Korea","institution_ids":["https://openalex.org/I88761825"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011760560","display_name":"Seung\u2010Ik Lee","orcid":"https://orcid.org/0000-0003-2986-7540"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]},{"id":"https://openalex.org/I88761825","display_name":"Korea University of Science and Technology","ror":"https://ror.org/000qzf213","country_code":"KR","type":"education","lineage":["https://openalex.org/I88761825"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seung-Ik Lee","raw_affiliation_strings":["Electronics and Telecommunications Research Institute, University of Science and Technology, Daejeon, South Korea","Electronics and Telecommunications Research Institute University of Science and Technology Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute, University of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I142401562","https://openalex.org/I88761825"]},{"raw_affiliation_string":"Electronics and Telecommunications Research Institute University of Science and Technology Daejeon, South Korea","institution_ids":["https://openalex.org/I142401562","https://openalex.org/I88761825"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5042350375"],"corresponding_institution_ids":["https://openalex.org/I88761825"],"apc_list":null,"apc_paid":null,"fwci":2.604,"has_fulltext":false,"cited_by_count":76,"citation_normalized_percentile":{"value":0.9,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"115","last_page":"118"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9958000183105469,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9757000207901001,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8312067985534668},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7828587293624878},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6647063493728638},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.626989483833313},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.5535163879394531},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.526047945022583},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5223214030265808},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.4681209623813629},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4598442316055298},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4461183547973633},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4294908344745636},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4244716465473175},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4110787808895111},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.36764511466026306},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33358460664749146},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08379939198493958}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8312067985534668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7828587293624878},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6647063493728638},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.626989483833313},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.5535163879394531},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.526047945022583},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5223214030265808},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.4681209623813629},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4598442316055298},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4461183547973633},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4294908344745636},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4244716465473175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4110787808895111},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.36764511466026306},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33358460664749146},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08379939198493958},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigcomp.2017.7881725","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigcomp.2017.7881725","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data and Smart Computing (BigComp)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G316595035","display_name":null,"funder_award_id":"B0101-15-0551","funder_id":"https://openalex.org/F4320322030","funder_display_name":"Ministry of Science, ICT and Future Planning"}],"funders":[{"id":"https://openalex.org/F4320322030","display_name":"Ministry of Science, ICT and Future Planning","ror":"https://ror.org/032e49973"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2024165284","https://openalex.org/W2079705627","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2131524184","https://openalex.org/W2149933564","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2167215970","https://openalex.org/W2406138340","https://openalex.org/W2950248853","https://openalex.org/W2962988160","https://openalex.org/W2963048316","https://openalex.org/W4299518610","https://openalex.org/W6637373629","https://openalex.org/W6679667936","https://openalex.org/W6682132143","https://openalex.org/W6684191040","https://openalex.org/W6684563725","https://openalex.org/W6685627644","https://openalex.org/W6713333156"],"related_works":["https://openalex.org/W4379256054","https://openalex.org/W2093953080","https://openalex.org/W47805180","https://openalex.org/W1967080779","https://openalex.org/W2963838862","https://openalex.org/W3015641590","https://openalex.org/W3216281372","https://openalex.org/W2612632602","https://openalex.org/W2949531434","https://openalex.org/W4286927328"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Networks":[2],"(CNNs)":[3],"has":[4],"shown":[5],"a":[6,20,43],"great":[7],"success":[8],"in":[9,32,80],"many":[10],"areas":[11],"including":[12],"complex":[13],"image":[14],"classification":[15],"tasks.":[16],"However,":[17],"they":[18],"need":[19],"lot":[21],"of":[22],"memory":[23,81],"and":[24,50,82],"computational":[25],"cost,":[26],"which":[27,62],"hinders":[28],"them":[29],"from":[30],"running":[31],"relatively":[33],"low-end":[34],"smart":[35,39],"devices":[36],"such":[37],"as":[38],"phones.":[40],"We":[41,54],"propose":[42,56],"CNN":[44],"compression":[45],"method":[46],"based":[47],"on":[48],"CP-decomposition":[49],"Tensor":[51],"Power":[52],"Method.":[53],"also":[55],"an":[57],"iterative":[58],"fine":[59],"tuning,":[60],"with":[61,92],"we":[63],"fine-tune":[64],"the":[65,75],"whole":[66],"network":[67],"after":[68],"decomposing":[69,74],"each":[70],"layer,":[71],"but":[72],"before":[73],"next":[76],"layer.":[77],"Significant":[78],"reduction":[79],"computation":[83],"cost":[84],"is":[85],"achieved":[86],"compared":[87],"to":[88],"state-of-the-art":[89],"previous":[90],"work":[91],"no":[93],"more":[94],"accuracy":[95],"loss.":[96]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":7}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
