{"id":"https://openalex.org/W4416251436","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228414","title":"RecLGB: Enhancing LightGBM using Recursive VAE with Mixed Attention for Time-Series Forecasting","display_name":"RecLGB: Enhancing LightGBM using Recursive VAE with Mixed Attention for Time-Series Forecasting","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251436","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228414"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228414","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228414","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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/A5102662845","display_name":"Yuxin Mei","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]},{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuxin Mei","raw_affiliation_strings":["East China Normal University,Shanghai Key Laboratory of Trustworthy Computing,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"East China Normal University,Shanghai Key Laboratory of Trustworthy Computing,Shanghai,China","institution_ids":["https://openalex.org/I4210139618","https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101714741","display_name":"Xu Han","orcid":"https://orcid.org/0000-0003-4573-0624"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]},{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Han","raw_affiliation_strings":["East China Normal University,Shanghai Key Laboratory of Trustworthy Computing,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"East China Normal University,Shanghai Key Laboratory of Trustworthy Computing,Shanghai,China","institution_ids":["https://openalex.org/I4210139618","https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047135195","display_name":"Zhongming Han","orcid":"https://orcid.org/0000-0003-0119-2828"},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongming Han","raw_affiliation_strings":["Beijing Technology and Business University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Technology and Business University,Beijing,China","institution_ids":["https://openalex.org/I179026463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101566937","display_name":"Li Han","orcid":"https://orcid.org/0000-0001-5797-2554"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]},{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Han","raw_affiliation_strings":["East China Normal University,Shanghai Key Laboratory of Trustworthy Computing,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"East China Normal University,Shanghai Key Laboratory of Trustworthy Computing,Shanghai,China","institution_ids":["https://openalex.org/I4210139618","https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100374998","display_name":"Jing Liu","orcid":"https://orcid.org/0000-0002-3588-2969"},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]},{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Liu","raw_affiliation_strings":["East China Normal University,Shanghai Key Laboratory of Trustworthy Computing,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"East China Normal University,Shanghai Key Laboratory of Trustworthy Computing,Shanghai,China","institution_ids":["https://openalex.org/I4210139618","https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102662845"],"corresponding_institution_ids":["https://openalex.org/I4210139618","https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.42144728,"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":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.23729999363422394,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.23729999363422394,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T13702","display_name":"Machine Learning in Healthcare","score":0.2054000049829483,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.15410000085830688,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.760200023651123},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7013000249862671},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6189000010490417},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5564000010490417},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49160000681877136},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4625000059604645},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.3952000141143799}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.762499988079071},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.760200023651123},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7013000249862671},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6531000137329102},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6189000010490417},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5564000010490417},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49160000681877136},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49160000681877136},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3952000141143799},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.36880001425743103},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3366999924182892},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29660001397132874},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2881999909877777},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2721000015735626},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.26249998807907104}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228414","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228414","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1902237438","https://openalex.org/W2028072219","https://openalex.org/W2069143585","https://openalex.org/W2100495367","https://openalex.org/W2338714606","https://openalex.org/W2613328025","https://openalex.org/W2808535700","https://openalex.org/W2890096158","https://openalex.org/W2963532813","https://openalex.org/W2988226917","https://openalex.org/W2998367712","https://openalex.org/W3171884590","https://openalex.org/W3174022889","https://openalex.org/W3177318507","https://openalex.org/W3199148273","https://openalex.org/W4200311493","https://openalex.org/W4210474990","https://openalex.org/W4378574837","https://openalex.org/W4382203079","https://openalex.org/W4392166795","https://openalex.org/W4400373628"],"related_works":[],"abstract_inverted_index":{"Time-series":[0],"forecasting":[1],"demands":[2],"efficient":[3],"modeling":[4,123],"of":[5],"long-range":[6],"dependencies":[7,71],"while":[8,68],"maintaining":[9],"computational":[10,95],"practicality.":[11],"Current":[12],"methods,":[13],"particularly":[14],"deep":[15,42,121],"learning":[16],"approaches,":[17],"often":[18],"struggle":[19],"with":[20,39,124],"complexity":[21],"and":[22,104,112],"scalability":[23],"when":[24],"handling":[25],"extensive":[26],"historical":[27,79],"sequences.":[28],"We":[29],"propose":[30],"RecLGB,":[31],"a":[32,40,49,56,128],"hybrid":[33],"framework":[34],"that":[35],"synergizes":[36],"LightGBM\u2019s":[37],"efficiency":[38],"memory-augmented":[41],"architecture.":[43],"At":[44],"its":[45],"core,":[46],"RecLGB":[47,97],"integrates":[48],"recursive":[50,75],"Variational":[51],"Autoencoder":[52],"(VAE)":[53],"enhanced":[54],"by":[55],"mixed":[57],"attention":[58],"mechanism,":[59],"which":[60],"preserves":[61],"temporal":[62],"order":[63],"through":[64],"linear":[65],"inductive":[66],"biases":[67],"dynamically":[69],"capturing":[70],"via":[72],"self-attention.":[73],"The":[74],"VAE":[76],"compresses":[77],"lengthy":[78],"sequences":[80],"into":[81],"compact":[82],"hierarchical":[83],"representations,":[84],"serving":[85],"as":[86],"an":[87],"external":[88],"memory":[89],"for":[90,132],"LightGBM":[91],"to":[92],"leverage":[93],"without":[94],"overload.":[96],"is":[98,136],"evaluated":[99],"on":[100],"five":[101],"real-world":[102],"datasets,":[103],"experiments":[105],"demonstrate":[106],"RecLGB\u2019s":[107],"superiority,":[108],"achieving":[109],"superior":[110],"accuracy":[111],"faster":[113],"inference":[114],"than":[115],"Transformer-based":[116],"baselines.":[117],"This":[118],"work":[119],"bridges":[120],"sequential":[122],"gradient-boosted":[125],"trees,":[126],"offering":[127],"scalable,":[129],"interpretable":[130],"solution":[131],"resource-constrained":[133],"forecasting.":[134],"Code":[135],"available":[137],"at:":[138],"https://github.com/Mayer-myx/RecLGB.":[139]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-14T00:00:00"}
