{"id":"https://openalex.org/W3045422318","doi":"https://doi.org/10.1109/dac18072.2020.9218501","title":"ALF: Autoencoder-based Low-rank Filter-sharing for Efficient Convolutional Neural Networks","display_name":"ALF: Autoencoder-based Low-rank Filter-sharing for Efficient Convolutional Neural Networks","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3045422318","doi":"https://doi.org/10.1109/dac18072.2020.9218501","mag":"3045422318"},"language":"en","primary_location":{"id":"doi:10.1109/dac18072.2020.9218501","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dac18072.2020.9218501","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 57th ACM/IEEE Design Automation Conference (DAC)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2007.13384","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047063939","display_name":"Alexander Frickenstein","orcid":null},"institutions":[{"id":"https://openalex.org/I1283382300","display_name":"BMW (Germany)","ror":"https://ror.org/05vs9tj88","country_code":"DE","type":"company","lineage":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]},{"id":"https://openalex.org/I4210156768","display_name":"BMW Group (Germany)","ror":"https://ror.org/044kkbh92","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210156768"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Alexander Frickenstein","raw_affiliation_strings":["Autonomous Driving, BMW Group, Munich, Germany","BMW Group,Autonomous Driving,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Autonomous Driving, BMW Group, Munich, Germany","institution_ids":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]},{"raw_affiliation_string":"BMW Group,Autonomous Driving,Munich,Germany","institution_ids":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037114730","display_name":"Manoj-Rohit Vemparala","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156768","display_name":"BMW Group (Germany)","ror":"https://ror.org/044kkbh92","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210156768"]},{"id":"https://openalex.org/I1283382300","display_name":"BMW (Germany)","ror":"https://ror.org/05vs9tj88","country_code":"DE","type":"company","lineage":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Manoj-Rohit Vemparala","raw_affiliation_strings":["Autonomous Driving, BMW Group, Munich, Germany","BMW Group,Autonomous Driving,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Autonomous Driving, BMW Group, Munich, Germany","institution_ids":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]},{"raw_affiliation_string":"BMW Group,Autonomous Driving,Munich,Germany","institution_ids":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085220085","display_name":"Nael Fasfous","orcid":"https://orcid.org/0000-0002-8081-7904"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Nael Fasfous","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Technical University of Munich, Munich, Germany","Technical University of Munich,Dept. of Electrical & Computer Engineering,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Technical University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Technical University of Munich,Dept. of Electrical & Computer Engineering,Munich,Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038840530","display_name":"Laura Hauenschild","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Laura Hauenschild","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Technical University of Munich, Munich, Germany","Technical University of Munich,Dept. of Electrical & Computer Engineering,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Technical University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Technical University of Munich,Dept. of Electrical & Computer Engineering,Munich,Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079890456","display_name":"Naveen-Shankar Nagaraja","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156768","display_name":"BMW Group (Germany)","ror":"https://ror.org/044kkbh92","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210156768"]},{"id":"https://openalex.org/I1283382300","display_name":"BMW (Germany)","ror":"https://ror.org/05vs9tj88","country_code":"DE","type":"company","lineage":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Naveen-Shankar Nagaraja","raw_affiliation_strings":["Autonomous Driving, BMW Group, Munich, Germany","BMW Group,Autonomous Driving,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Autonomous Driving, BMW Group, Munich, Germany","institution_ids":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]},{"raw_affiliation_string":"BMW Group,Autonomous Driving,Munich,Germany","institution_ids":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034106438","display_name":"Christian Unger","orcid":null},"institutions":[{"id":"https://openalex.org/I1283382300","display_name":"BMW (Germany)","ror":"https://ror.org/05vs9tj88","country_code":"DE","type":"company","lineage":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]},{"id":"https://openalex.org/I4210156768","display_name":"BMW Group (Germany)","ror":"https://ror.org/044kkbh92","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210156768"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian Unger","raw_affiliation_strings":["Autonomous Driving, BMW Group, Munich, Germany","BMW Group,Autonomous Driving,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Autonomous Driving, BMW Group, Munich, Germany","institution_ids":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]},{"raw_affiliation_string":"BMW Group,Autonomous Driving,Munich,Germany","institution_ids":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005732789","display_name":"Walter Stechele","orcid":"https://orcid.org/0000-0002-7455-8483"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Walter Stechele","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Technical University of Munich, Munich, Germany","Technical University of Munich,Dept. of Electrical & Computer Engineering,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Technical University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Technical University of Munich,Dept. of Electrical & Computer Engineering,Munich,Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5047063939"],"corresponding_institution_ids":["https://openalex.org/I1283382300","https://openalex.org/I4210156768"],"apc_list":null,"apc_paid":null,"fwci":0.0981,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.39409301,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9987000226974487,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9987000226974487,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9986000061035156,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9980000257492065,"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/autoencoder","display_name":"Autoencoder","score":0.8166066408157349},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.7986631989479065},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.796695351600647},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7104886174201965},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.674798846244812},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6418401002883911},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5712993144989014},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4905533194541931},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4676280617713928},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4540390372276306},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45149749517440796},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.44296568632125854},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44117873907089233},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.07898390293121338}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8166066408157349},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.7986631989479065},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.796695351600647},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7104886174201965},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.674798846244812},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6418401002883911},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5712993144989014},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4905533194541931},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4676280617713928},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4540390372276306},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45149749517440796},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.44296568632125854},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44117873907089233},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.07898390293121338},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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":4,"locations":[{"id":"doi:10.1109/dac18072.2020.9218501","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dac18072.2020.9218501","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 57th ACM/IEEE Design Automation Conference (DAC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2007.13384","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.13384","pdf_url":"https://arxiv.org/pdf/2007.13384","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3045422318","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2007.13384.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2007.13384","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2007.13384","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2007.13384","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.13384","pdf_url":"https://arxiv.org/pdf/2007.13384","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3045422318.pdf","grobid_xml":"https://content.openalex.org/works/W3045422318.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1677182931","https://openalex.org/W2097117768","https://openalex.org/W2104636679","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2267635276","https://openalex.org/W2279098554","https://openalex.org/W2442974303","https://openalex.org/W2550831128","https://openalex.org/W2565305208","https://openalex.org/W2886851211","https://openalex.org/W2891735857","https://openalex.org/W2899818272","https://openalex.org/W2924498682","https://openalex.org/W2928560789","https://openalex.org/W2940862705","https://openalex.org/W2963140066","https://openalex.org/W2963674932","https://openalex.org/W2963918968","https://openalex.org/W2963981420","https://openalex.org/W2964259004","https://openalex.org/W2965851570","https://openalex.org/W2995607862","https://openalex.org/W3036058978","https://openalex.org/W3090169770","https://openalex.org/W4249932213","https://openalex.org/W6631943919","https://openalex.org/W6638632666","https://openalex.org/W6693397755","https://openalex.org/W6724998850","https://openalex.org/W6754873534","https://openalex.org/W6756887525","https://openalex.org/W6760775249","https://openalex.org/W6769906912"],"related_works":["https://openalex.org/W3092479081","https://openalex.org/W3047947467","https://openalex.org/W3036882359","https://openalex.org/W2614143469","https://openalex.org/W2891862962","https://openalex.org/W2918653705","https://openalex.org/W2965851570","https://openalex.org/W2784596704","https://openalex.org/W3164316977","https://openalex.org/W2962851801","https://openalex.org/W3177323033","https://openalex.org/W2951399001","https://openalex.org/W3164522330","https://openalex.org/W2969396878","https://openalex.org/W3123482262","https://openalex.org/W2903611708","https://openalex.org/W3186120077","https://openalex.org/W2998474000","https://openalex.org/W2946340800","https://openalex.org/W3111941549"],"abstract_inverted_index":{"Closing":[0],"the":[1,4,13,20,77,93],"gap":[2],"between":[3],"hardware":[5,86],"requirements":[6],"of":[7,34,79,134],"state-of-the-art":[8,108],"convolutional":[9],"neural":[10,36],"networks":[11,37],"and":[12,31,142],"limited":[14],"resources":[15],"constraining":[16],"embedded":[17,85],"applications":[18,83],"is":[19,105],"next":[21],"big":[22],"challenge":[23],"in":[24,43,71,136,140,144,150],"deep":[25,81],"learning":[26,82],"research.":[27],"The":[28],"computational":[29],"complexity":[30],"memory":[32],"footprint":[33],"such":[35,50],"are":[38,53],"typically":[39],"daunting":[40],"for":[41,59],"deployment":[42],"resource":[44],"constrained":[45],"environments.":[46],"Model":[47],"compression":[48,114],"techniques,":[49],"as":[51,119,121],"pruning,":[52],"emphasized":[54],"among":[55],"other":[56],"optimization":[57],"methods":[58],"solving":[60],"this":[61,89],"problem.":[62],"Most":[63],"existing":[64],"techniques":[65],"require":[66],"domain":[67],"expertise":[68],"or":[69],"result":[70],"irregular":[72],"sparse":[73],"representations,":[74],"which":[75],"increase":[76],"burden":[78],"deploying":[80],"on":[84,116,122],"accelerators.":[87],"In":[88,127],"paper,":[90],"we":[91],"propose":[92],"autoencoder-based":[94],"low-rank":[95],"filter-sharing":[96],"technique":[97],"(ALF).":[98],"When":[99],"applied":[100],"to":[101,107],"various":[102],"networks,":[103],"ALF":[104,130],"compared":[106],"pruning":[109],"methods,":[110],"demonstrating":[111],"its":[112],"efficient":[113],"capabilities":[115],"theoretical":[117],"metrics":[118],"well":[120],"an":[123],"accurate,":[124],"deterministic":[125],"hardware-model.":[126],"our":[128],"experiments,":[129],"showed":[131],"a":[132],"reduction":[133],"70%":[135],"network":[137],"parameters,":[138],"61%":[139],"operations":[141],"41%":[143],"execution":[145],"time,":[146],"with":[147],"minimal":[148],"loss":[149],"accuracy.":[151]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
