{"id":"https://openalex.org/W2920912927","doi":"https://doi.org/10.1109/tnnls.2019.2899386","title":"GeCo: Classification Restricted Boltzmann Machine Hardware for On-Chip Semisupervised Learning and Bayesian Inference","display_name":"GeCo: Classification Restricted Boltzmann Machine Hardware for On-Chip Semisupervised Learning and Bayesian Inference","publication_year":2019,"publication_date":"2019-03-15","ids":{"openalex":"https://openalex.org/W2920912927","doi":"https://doi.org/10.1109/tnnls.2019.2899386","mag":"2920912927","pmid":"https://pubmed.ncbi.nlm.nih.gov/30892240"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2019.2899386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2899386","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5008474646","display_name":"Wooseok Yi","orcid":null},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Wooseok Yi","raw_affiliation_strings":["Department of Creative IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Creative IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang, South Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089337265","display_name":"Junki Park","orcid":"https://orcid.org/0000-0001-5662-657X"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junki Park","raw_affiliation_strings":["Department of Creative IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Creative IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang, South Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003219699","display_name":"Jae\u2010Joon Kim","orcid":"https://orcid.org/0000-0001-5175-8258"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae-Joon Kim","raw_affiliation_strings":["Department of Creative IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-5175-8258","affiliations":[{"raw_affiliation_string":"Department of Creative IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang, South Korea","institution_ids":["https://openalex.org/I123900574"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008474646"],"corresponding_institution_ids":["https://openalex.org/I123900574"],"apc_list":null,"apc_paid":null,"fwci":1.0211,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.80414906,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"31","issue":"1","first_page":"53","last_page":"65"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9997000098228455,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9997000098228455,"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":0.9984999895095825,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9980000257492065,"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":0.7473369240760803},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6915905475616455},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6740548610687256},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6067776679992676},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5753533840179443},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.5205910205841064},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.48603588342666626},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46607160568237305},{"id":"https://openalex.org/keywords/boltzmann-machine","display_name":"Boltzmann machine","score":0.44583818316459656},{"id":"https://openalex.org/keywords/restricted-boltzmann-machine","display_name":"Restricted Boltzmann machine","score":0.4422720670700073},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43479758501052856},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4256637692451477},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.360391229391098},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.13401949405670166}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7473369240760803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6915905475616455},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6740548610687256},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6067776679992676},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5753533840179443},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.5205910205841064},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.48603588342666626},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46607160568237305},{"id":"https://openalex.org/C192576344","wikidata":"https://www.wikidata.org/wiki/Q194706","display_name":"Boltzmann machine","level":3,"score":0.44583818316459656},{"id":"https://openalex.org/C199354608","wikidata":"https://www.wikidata.org/wiki/Q7316287","display_name":"Restricted Boltzmann machine","level":3,"score":0.4422720670700073},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43479758501052856},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4256637692451477},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.360391229391098},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.13401949405670166}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2019.2899386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2899386","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:30892240","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30892240","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:oasis.postech.ac.kr:2014.oak/105629","is_oa":false,"landing_page_url":"https://oasis.postech.ac.kr/handle/2014.oak/105629","pdf_url":null,"source":{"id":"https://openalex.org/S4306401965","display_name":"Open Access System for Information Sharing (Pohang University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I123900574","host_organization_name":"Pohang University of Science and Technology","host_organization_lineage":["https://openalex.org/I123900574"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G402045675","display_name":null,"funder_award_id":"IITP-2018-2011-1-00783","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W4919037","https://openalex.org/W587794757","https://openalex.org/W1494192115","https://openalex.org/W1545825812","https://openalex.org/W1579590535","https://openalex.org/W1981364124","https://openalex.org/W2002700944","https://openalex.org/W2105577021","https://openalex.org/W2108379813","https://openalex.org/W2115639406","https://openalex.org/W2116064496","https://openalex.org/W2116754965","https://openalex.org/W2119144962","https://openalex.org/W2136246134","https://openalex.org/W2136922672","https://openalex.org/W2138857742","https://openalex.org/W2141125852","https://openalex.org/W2147336195","https://openalex.org/W2153939756","https://openalex.org/W2163614729","https://openalex.org/W2171318387","https://openalex.org/W2194321275","https://openalex.org/W2286256158","https://openalex.org/W2334805829","https://openalex.org/W2344661575","https://openalex.org/W2460553511","https://openalex.org/W2592844773","https://openalex.org/W2596906311","https://openalex.org/W2613789569","https://openalex.org/W2791280507","https://openalex.org/W2964299589","https://openalex.org/W6600213771","https://openalex.org/W6617368339","https://openalex.org/W6651360156","https://openalex.org/W6675770872","https://openalex.org/W6680300913","https://openalex.org/W6683915439","https://openalex.org/W6695934027"],"related_works":["https://openalex.org/W2952018105","https://openalex.org/W2916681395","https://openalex.org/W4283272532","https://openalex.org/W2119341610","https://openalex.org/W2556473569","https://openalex.org/W2193475944","https://openalex.org/W4302433642","https://openalex.org/W2529583158","https://openalex.org/W2551541394","https://openalex.org/W2892911634"],"abstract_inverted_index":{"The":[0,156],"probabilistic":[1],"Bayesian":[2,35,154],"inference":[3,36,180],"of":[4,15,43,62,85,133,146,149,171,182],"real-time":[5],"input":[6,54],"data":[7,175],"is":[8,18,39,74,104,187],"becoming":[9],"more":[10],"popular,":[11],"and":[12,34,51,153,173,195],"the":[13,83,89,98,131,137,144,179,183,206,211,227],"importance":[14],"semisupervised":[16,32,202],"learning":[17,33,139,193,203],"growing.":[19],"We":[20,94],"present":[21],"a":[22,40,147,160,167,191,199,217],"classification":[23,49],"restricted":[24],"Boltzmann":[25],"machine":[26],"(ClassRBM)-based":[27],"hardware":[28,63,214],"accelerator":[29],"with":[30],"on-chip":[31],"capability.":[37],"ClassRBM":[38,56,141],"specific":[41],"type":[42],"Markov":[44,150],"network":[45],"that":[46,97,129,178],"can":[47],"perform":[48],"tasks":[50],"reconstruct":[52],"its":[53,72],"data.":[55],"has":[57],"several":[58],"advantages":[59],"in":[60,113,143],"terms":[61],"implementation":[64],"compared":[65,77],"to":[66,78,107],"other":[67],"backpropagation-based":[68,79],"neural":[69],"networks.":[70],"However,":[71],"accuracy":[73,84,132,181],"relatively":[75],"low":[76],"learning.":[80],"To":[81],"improve":[82],"ClassRBM,":[86],"we":[87,120],"propose":[88,121],"multi-neuron-per-class":[90],"(multi-NPC)":[91],"voting":[92],"scheme.":[93],"also":[95],"reveal":[96],"contrastive":[99,124],"divergence":[100,125],"(CD)":[101],"algorithm,":[102,140],"which":[103],"commonly":[105],"used":[106],"train":[108],"RBM,":[109],"shows":[110],"poor":[111],"performance":[112],"this":[114],"multi-NPC":[115,134],"ClassRBM.":[116,135],"As":[117],"an":[118,122],"alternative,":[119],"asymmetric":[123],"(ACD)":[126],"training":[127,152],"algorithm":[128,186],"improves":[130],"With":[136],"ACD":[138,185],"operates":[142],"form":[145],"combination":[148],"Chain":[151],"inference.":[155],"experimental":[157],"results":[158],"on":[159,216,230],"field-programmable":[161],"gate":[162],"array":[163],"(FPGA)":[164],"board":[165,221],"for":[166,190,198],"Modified":[168],"National":[169],"Institute":[170],"Standards":[172],"Technology":[174],"set":[176],"confirm":[177],"proposed":[184],"5.82%":[188],"higher":[189,197],"supervised":[192],"case":[194,204],"12.78%":[196],"1%":[200],"labeled":[201],"than":[205,226],"conventional":[207],"CD":[208],"algorithm.":[209],"Also,":[210],"GeCo":[212],"ver.2":[213],"implemented":[215],"Xilinx":[218],"ZCU102":[219],"FPGA":[220],"was":[222],"349.04":[223],"times":[224],"faster":[225],"C":[228],"simulation":[229],"CPU.":[231]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}