{"id":"https://openalex.org/W3200923927","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533677","title":"Low-Resource Neural Machine Translation with Neural Episodic Control","display_name":"Low-Resource Neural Machine Translation with Neural Episodic Control","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200923927","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533677","mag":"3200923927"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533677","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5101137547","display_name":"Nier Wu","orcid":"https://orcid.org/0009-0006-2521-4058"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nier Wu","raw_affiliation_strings":["College of Computer Science-College of Software, Inner Mongolia University, Hohhot, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science-College of Software, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053521242","display_name":"Hongxu Hou","orcid":"https://orcid.org/0009-0005-4314-4527"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxu Hou","raw_affiliation_strings":["College of Computer Science-College of Software, Inner Mongolia University, Hohhot, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science-College of Software, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004036450","display_name":"Shuo Sun","orcid":"https://orcid.org/0000-0001-7153-1878"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Sun","raw_affiliation_strings":["College of Computer Science-College of Software, Inner Mongolia University, Hohhot, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science-College of Software, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101513399","display_name":"Wei Zheng","orcid":"https://orcid.org/0000-0001-8921-5304"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zheng","raw_affiliation_strings":["College of Computer Science-College of Software, Inner Mongolia University, Hohhot, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science-College of Software, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101137547"],"corresponding_institution_ids":["https://openalex.org/I2722730"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1329047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9948999881744385,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9948999881744385,"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/T10028","display_name":"Topic Modeling","score":0.9745000004768372,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9607999920845032,"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/computer-science","display_name":"Computer science","score":0.7658424377441406},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6941137313842773},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.6625451445579529},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6077718138694763},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.5994659066200256},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5942307710647583},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5931580066680908},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47358089685440063},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.464758038520813},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.43796175718307495},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41214191913604736},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1223902702331543},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08984532952308655}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7658424377441406},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6941137313842773},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.6625451445579529},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6077718138694763},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.5994659066200256},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5942307710647583},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5931580066680908},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47358089685440063},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.464758038520813},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.43796175718307495},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41214191913604736},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1223902702331543},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08984532952308655},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533677","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.550000011920929}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1753482797","https://openalex.org/W2017338426","https://openalex.org/W2101105183","https://openalex.org/W2119717200","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2487501366","https://openalex.org/W2552839021","https://openalex.org/W2597655663","https://openalex.org/W2601324753","https://openalex.org/W2604763608","https://openalex.org/W2888442053","https://openalex.org/W2888541716","https://openalex.org/W2963386218","https://openalex.org/W2963403868","https://openalex.org/W2964308564","https://openalex.org/W2964352247","https://openalex.org/W3096550769","https://openalex.org/W4298406109","https://openalex.org/W4385245566","https://openalex.org/W6637698695","https://openalex.org/W6679434410","https://openalex.org/W6679436768","https://openalex.org/W6722524744","https://openalex.org/W6735377749","https://openalex.org/W6736057607","https://openalex.org/W6737845164","https://openalex.org/W6739901393","https://openalex.org/W6898505805"],"related_works":["https://openalex.org/W4285277090","https://openalex.org/W4327738859","https://openalex.org/W2348722996","https://openalex.org/W2334570605","https://openalex.org/W3181683615","https://openalex.org/W1633485514","https://openalex.org/W1980454230","https://openalex.org/W1604739066","https://openalex.org/W4362501864","https://openalex.org/W2898767136"],"abstract_inverted_index":{"Reinforcement":[0],"Learning":[1],"(RL)":[2],"has":[3],"been":[4],"proved":[5],"to":[6,105],"alleviate":[7],"metric":[8],"inconsistency":[9],"and":[10,34,83,119,123],"exposure":[11],"deviation":[12],"in":[13],"training-evaluation":[14],"of":[15,138],"neural":[16,93],"machine":[17],"translation":[18],"(NMT),":[19],"but":[20],"the":[21,39,57,73,80,85,96,101,124,128,136,139],"sample":[22],"efficiency":[23],"is":[24],"limited":[25],"by":[26,44,89],"sampling":[27],"methods":[28],"(Temporal-Difference":[29],"(TD)":[30],"or":[31],"Monte-Carlo":[32],"(MC)),":[33],"still":[35],"cannot":[36],"compensate":[37],"for":[38],"inefficient":[40],"non-zero":[41],"rewards":[42,51],"caused":[43],"insufficient":[45],"data":[46],"sets.":[47],"In":[48],"addition,":[49],"RL":[50],"can":[52,98],"only":[53],"be":[54],"effective":[55],"when":[56,108],"model":[58,74,97],"parameters":[59,78],"are":[60],"basically":[61,76],"determined.":[62],"Therefore,":[63],"we":[64],"proposed":[65],"episodic":[66],"control":[67],"reinforcement":[68],"learning":[69],"method,":[70],"which":[71,133],"obtains":[72],"with":[75],"determined":[77],"through":[79],"knowledge":[81],"transfer,":[82],"records":[84],"historical":[86],"action":[87],"trajectory":[88],"introducing":[90],"semi-tabular":[91],"differentiable":[92],"dictionary":[94],"(DND),":[95],"quickly":[99],"approximate":[100],"real":[102],"state-value":[103],"according":[104],"samples":[106],"reward":[107],"updating":[109],"policy.":[110],"We":[111],"verified":[112],"on":[113],"CCMT2019":[114],"Mongolian-Chinese":[115],"(Mo-Zh),":[116],"Tibetan-Chinese":[117],"(Ti-Zh),":[118],"Uyghur-Chinese":[120],"(Ug-Zh)":[121],"tasks,":[122],"results":[125],"showed":[126],"that":[127],"quality":[129],"was":[130],"significantly":[131],"improved,":[132],"fully":[134],"demonstrated":[135],"effectiveness":[137],"method.":[140]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}