{"id":"https://openalex.org/W2943042662","doi":"https://doi.org/10.1109/iscas.2019.8702253","title":"Stochastic Learning with Back Propagation","display_name":"Stochastic Learning with Back Propagation","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2943042662","doi":"https://doi.org/10.1109/iscas.2019.8702253","mag":"2943042662"},"language":"en","primary_location":{"id":"doi:10.1109/iscas.2019.8702253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2019.8702253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5089830521","display_name":"Guhyun Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I58716616","display_name":"Korea Institute of Science and Technology","ror":"https://ror.org/05kzfa883","country_code":"KR","type":"facility","lineage":["https://openalex.org/I27494661","https://openalex.org/I2801339556","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098","https://openalex.org/I4387152098","https://openalex.org/I58716616"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Guhyun Kim","raw_affiliation_strings":["Center for electronic materials, Korea Institute of Science and Technology, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for electronic materials, Korea Institute of Science and Technology, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I58716616"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027075775","display_name":"Cheol Seong Hwang","orcid":"https://orcid.org/0000-0002-6254-9758"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Cheol Seong Hwang","raw_affiliation_strings":["School of Materials Science and Engineering, Seoul National University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Materials Science and Engineering, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082971950","display_name":"Doo Seok Jeong","orcid":"https://orcid.org/0000-0001-7954-2213"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Doo Seok Jeong","raw_affiliation_strings":["Division of Materials Science and Engineering, Hanyang university, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Materials Science and Engineering, Hanyang university, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I4575257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.195,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72846299,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"25","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9987999796867371,"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/autoencoder","display_name":"Autoencoder","score":0.8652777075767517},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.8081247806549072},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7394911050796509},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.661431610584259},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6375338435173035},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5712689161300659},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4703129827976227},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.44524121284484863},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4205819368362427},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4123850166797638},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3686917722225189},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34843337535858154},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11126255989074707}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8652777075767517},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.8081247806549072},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7394911050796509},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.661431610584259},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6375338435173035},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5712689161300659},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4703129827976227},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.44524121284484863},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4205819368362427},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4123850166797638},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3686917722225189},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34843337535858154},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11126255989074707},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iscas.2019.8702253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2019.8702253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"},{"id":"pmh:oai:s-space.snu.ac.kr:10371/186497","is_oa":false,"landing_page_url":"https://hdl.handle.net/10371/186497","pdf_url":null,"source":{"id":"https://openalex.org/S4306401345","display_name":"Seoul National University Open Repository (Seoul National University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139264467","host_organization_name":"Seoul National University","host_organization_lineage":["https://openalex.org/I139264467"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Proceedings Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1542981317","https://openalex.org/W1998177673","https://openalex.org/W2025768430","https://openalex.org/W2075948878","https://openalex.org/W2120432001","https://openalex.org/W2145287260","https://openalex.org/W2145339207","https://openalex.org/W2156387975","https://openalex.org/W2248832573","https://openalex.org/W2257979135","https://openalex.org/W2312605586","https://openalex.org/W2404581299","https://openalex.org/W2480295938","https://openalex.org/W2518320872","https://openalex.org/W2782791387","https://openalex.org/W3003193617","https://openalex.org/W6681342084","https://openalex.org/W6682889407"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000","https://openalex.org/W3037110488"],"abstract_inverted_index":{"Despite":[0],"of":[1,26,48,51],"remarkable":[2],"progress":[3],"on":[4],"deep":[5,11,19],"learning,":[6],"its":[7],"hardware":[8],"implementation":[9],"beyond":[10],"learning":[12,20,28,34,39],"acceleration":[13],"is":[14,79],"still":[15],"behind":[16],"the":[17,37,67,76,96,110],"software":[18],"due":[21],"in":[22,59,81,99,102,117],"part":[23],"to":[24,56,89],"lack":[25],"hardware-compatible":[27],"algorithm.":[29,129],"In":[30],"this":[31],"paper,":[32],"a":[33,60,82,91,122,127],"method":[35],"called":[36],"stochastic":[38,83],"with":[40,121],"backpropagation":[41,128],"(SLBP)":[42],"algorithm":[43,69,86,112],"was":[44,87],"proposed.":[45],"The":[46,85],"network":[47],"concern":[49],"consists":[50],"ternary":[52],"synaptic":[53],"weight,":[54],"favorable":[55],"be":[57],"implemented":[58],"resistance-based":[61],"crossbar":[62],"array.":[63],"Every":[64],"training":[65],"epoch,":[66],"SLBP":[68,111],"evaluates":[70],"weight":[71,78],"update":[72],"probability":[73],"at":[74],"which":[75,94],"corresponding":[77],"updated":[80],"manner.":[84],"used":[88],"train":[90],"denoising":[92],"autoencoder,":[93],"identified":[95],"successful":[97],"reduction":[98,116],"noise":[100],"(increase":[101],"peak":[103],"signal-to-noise":[104],"ratio":[105],"by":[106],"approximately":[107],"68%).":[108],"Notably,":[109],"achieves":[113],"an":[114],"86%":[115],"memory":[118],"usage":[119],"compared":[120],"real-valued":[123],"autoencoder":[124],"trained":[125],"using":[126]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-08-27T14:10:00.468798","created_date":"2025-10-10T00:00:00"}
