{"id":"https://openalex.org/W3015959685","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207550","title":"Continual Learning with Gated Incremental Memories for sequential data processing","display_name":"Continual Learning with Gated Incremental Memories for sequential data processing","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3015959685","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207550","mag":"3015959685"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9207550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2004.04077","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051270952","display_name":"Andrea Cossu","orcid":"https://orcid.org/0000-0002-4874-8830"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Andrea Cossu","raw_affiliation_strings":["Computer Science Dept., University of Pisa, Pisa, Italy"],"affiliations":[{"raw_affiliation_string":"Computer Science Dept., University of Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041806564","display_name":"Antonio Carta","orcid":"https://orcid.org/0000-0002-0003-2323"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Antonio Carta","raw_affiliation_strings":["Computer Science Dept., University of Pisa, Pisa, Italy"],"affiliations":[{"raw_affiliation_string":"Computer Science Dept., University of Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053890378","display_name":"Davide Bacciu","orcid":"https://orcid.org/0000-0001-5213-2468"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Davide Bacciu","raw_affiliation_strings":["Computer Science Dept., University of Pisa, Pisa, Italy"],"affiliations":[{"raw_affiliation_string":"Computer Science Dept., University of Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051270952"],"corresponding_institution_ids":["https://openalex.org/I108290504"],"apc_list":null,"apc_paid":null,"fwci":3.017,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.92788055,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9790999889373779,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9739999771118164,"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/forgetting","display_name":"Forgetting","score":0.8695679903030396},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7956351041793823},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.681492269039154},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6794913411140442},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5869078636169434},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.5515395402908325},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5125839114189148},{"id":"https://openalex.org/keywords/enabling","display_name":"Enabling","score":0.5072826743125916},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47306811809539795},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.46981385350227356},{"id":"https://openalex.org/keywords/consolidation","display_name":"Consolidation (business)","score":0.4549441337585449},{"id":"https://openalex.org/keywords/sequence-learning","display_name":"Sequence learning","score":0.4432377219200134},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.43325144052505493},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4225269854068756},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4206109941005707},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3707153797149658}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.8695679903030396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7956351041793823},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.681492269039154},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6794913411140442},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5869078636169434},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.5515395402908325},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5125839114189148},{"id":"https://openalex.org/C22607594","wikidata":"https://www.wikidata.org/wiki/Q5375150","display_name":"Enabling","level":2,"score":0.5072826743125916},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47306811809539795},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.46981385350227356},{"id":"https://openalex.org/C2776014549","wikidata":"https://www.wikidata.org/wiki/Q3050847","display_name":"Consolidation (business)","level":2,"score":0.4549441337585449},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.4432377219200134},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.43325144052505493},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4225269854068756},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4206109941005707},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3707153797149658},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9207550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2004.04077","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2004.04077","pdf_url":"https://arxiv.org/pdf/2004.04077","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":"pmh:oai:arpi.unipi.it:11568/1078269","is_oa":false,"landing_page_url":"http://hdl.handle.net/11568/1078269","pdf_url":null,"source":{"id":"https://openalex.org/S4377196265","display_name":"CINECA IRIS Institutial research information system (University of Pisa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I108290504","host_organization_name":"University of Pisa","host_organization_lineage":["https://openalex.org/I108290504"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2004.04077","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2004.04077","pdf_url":"https://arxiv.org/pdf/2004.04077","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":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W139044672","https://openalex.org/W1522301498","https://openalex.org/W1525859397","https://openalex.org/W1551045851","https://openalex.org/W1636521571","https://openalex.org/W1904826605","https://openalex.org/W1977544285","https://openalex.org/W1999038366","https://openalex.org/W2004459864","https://openalex.org/W2022775778","https://openalex.org/W2060277733","https://openalex.org/W2064675550","https://openalex.org/W2099419573","https://openalex.org/W2112796928","https://openalex.org/W2116435618","https://openalex.org/W2116522068","https://openalex.org/W2133088989","https://openalex.org/W2165310684","https://openalex.org/W2183208319","https://openalex.org/W2282186389","https://openalex.org/W2426267443","https://openalex.org/W2474920236","https://openalex.org/W2554616628","https://openalex.org/W2554957561","https://openalex.org/W2557389081","https://openalex.org/W2560647685","https://openalex.org/W2587753047","https://openalex.org/W2593116425","https://openalex.org/W2737492962","https://openalex.org/W2743151379","https://openalex.org/W2788388592","https://openalex.org/W2899243567","https://openalex.org/W2901159965","https://openalex.org/W2963540014","https://openalex.org/W2963560049","https://openalex.org/W2963755273","https://openalex.org/W2963992014","https://openalex.org/W2964121744","https://openalex.org/W2964199361","https://openalex.org/W2964304579","https://openalex.org/W2972429060","https://openalex.org/W2972566450","https://openalex.org/W2972845325","https://openalex.org/W2983826605","https://openalex.org/W2994886105","https://openalex.org/W3001063045","https://openalex.org/W3023802502","https://openalex.org/W3102015031","https://openalex.org/W4241336979","https://openalex.org/W4255466416","https://openalex.org/W4301163820","https://openalex.org/W4319988532","https://openalex.org/W6605683200","https://openalex.org/W6631190155","https://openalex.org/W6631621112","https://openalex.org/W6677326919","https://openalex.org/W6686490978","https://openalex.org/W6720565605","https://openalex.org/W6730235532","https://openalex.org/W6741217325","https://openalex.org/W6742852309","https://openalex.org/W6756484865","https://openalex.org/W6757283395","https://openalex.org/W6785333560","https://openalex.org/W6849896277"],"related_works":["https://openalex.org/W4289718052","https://openalex.org/W2164121020","https://openalex.org/W1974860256","https://openalex.org/W2145559838","https://openalex.org/W2905319430","https://openalex.org/W3116498279","https://openalex.org/W2014032771","https://openalex.org/W2597948870","https://openalex.org/W2428505524","https://openalex.org/W2962722950"],"abstract_inverted_index":{"The":[0],"ability":[1],"to":[2,68,123,145],"learn":[3],"in":[4,39,73,148],"dynamic,":[5],"nonstationary":[6],"environments":[7],"without":[8,76],"forgetting":[9,77],"previous":[10],"knowledge,":[11],"also":[12,82],"known":[13],"as":[14],"Continual":[15],"Learning":[16],"(CL),":[17],"is":[18,36,47,66],"a":[19,57,86,116],"key":[20],"enabler":[21],"for":[22,50,63,141],"scalable":[23],"and":[24,42,84,113,137],"trustworthy":[25],"deployments":[26],"of":[27,33,96,100,107,118,134],"adaptive":[28],"solutions.":[29],"While":[30],"the":[31,105,124,131,139],"importance":[32],"continual":[34],"learning":[35,44],"largely":[37],"acknowledged":[38],"machine":[40],"vision":[41],"reinforcement":[43],"problems,":[45],"this":[46],"mostly":[48],"under-documented":[49],"sequence":[51],"processing":[52,127],"tasks.":[53],"This":[54],"work":[55],"proposes":[56],"Recurrent":[58],"Neural":[59],"Network":[60],"(RNN)":[61],"model":[62],"CL":[64,88,120,147],"that":[65],"able":[67],"deal":[69],"with":[70],"concept":[71],"drift":[72],"input":[74],"distribution":[75],"previously":[78],"acquired":[79],"knowledge.":[80],"We":[81],"implement":[83],"test":[85],"popular":[87],"approach,":[89],"Elastic":[90],"Weight":[91],"Consolidation":[92],"(EWC),":[93],"on":[94,115],"top":[95],"two":[97],"different":[98],"types":[99],"RNNs.":[101,149],"Finally,":[102],"we":[103],"compare":[104],"performances":[106],"our":[108,135],"enhanced":[109],"architecture":[110,136],"against":[111],"EWC":[112],"RNNs":[114],"set":[117],"standard":[119],"benchmarks,":[121],"adapted":[122],"sequential":[125],"data":[126],"scenario.":[128],"Results":[129],"show":[130],"superior":[132],"performance":[133],"highlight":[138],"need":[140],"special":[142],"solutions":[143],"designed":[144],"address":[146]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}