{"id":"https://openalex.org/W4401980011","doi":"https://doi.org/10.1109/lca.2024.3445948","title":"Proactive Embedding on Cold Data for Deep Learning Recommendation Model Training","display_name":"Proactive Embedding on Cold Data for Deep Learning Recommendation Model Training","publication_year":2024,"publication_date":"2024-07-01","ids":{"openalex":"https://openalex.org/W4401980011","doi":"https://doi.org/10.1109/lca.2024.3445948"},"language":"en","primary_location":{"id":"doi:10.1109/lca.2024.3445948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lca.2024.3445948","pdf_url":null,"source":{"id":"https://openalex.org/S17643076","display_name":"IEEE Computer Architecture Letters","issn_l":"1556-6056","issn":["1556-6056","1556-6064","2473-2575"],"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 Computer Architecture Letters","raw_type":"journal-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/A5063213318","display_name":"Haeyoon Cho","orcid":"https://orcid.org/0009-0008-2879-1568"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Haeyoon Cho","raw_affiliation_strings":["School of Electrical Engineering, KAIST, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073862089","display_name":"Hyojun Son","orcid":"https://orcid.org/0000-0002-5199-9139"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyojun Son","raw_affiliation_strings":["School of Electrical Engineering, KAIST, Daejeon, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-5199-9139","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012713127","display_name":"Jungmin Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I134353371","display_name":"SK Group (South Korea)","ror":"https://ror.org/03696td91","country_code":"KR","type":"company","lineage":["https://openalex.org/I134353371"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jungmin Choi","raw_affiliation_strings":["SK Hynix, Icheon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SK Hynix, Icheon, South Korea","institution_ids":["https://openalex.org/I134353371"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057758277","display_name":"Byungil Koh","orcid":"https://orcid.org/0000-0002-1110-9971"},"institutions":[{"id":"https://openalex.org/I134353371","display_name":"SK Group (South Korea)","ror":"https://ror.org/03696td91","country_code":"KR","type":"company","lineage":["https://openalex.org/I134353371"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Byungil Koh","raw_affiliation_strings":["SK Hynix, Icheon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SK Hynix, Icheon, South Korea","institution_ids":["https://openalex.org/I134353371"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002544158","display_name":"Minho Ha","orcid":"https://orcid.org/0000-0002-9940-072X"},"institutions":[{"id":"https://openalex.org/I134353371","display_name":"SK Group (South Korea)","ror":"https://ror.org/03696td91","country_code":"KR","type":"company","lineage":["https://openalex.org/I134353371"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minho Ha","raw_affiliation_strings":["SK Hynix, Icheon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SK Hynix, Icheon, South Korea","institution_ids":["https://openalex.org/I134353371"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100698124","display_name":"John Kim","orcid":"https://orcid.org/0000-0003-3958-3891"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"John Kim","raw_affiliation_strings":["School of Electrical Engineering, KAIST, Daejeon, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-3958-3891","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5063213318"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.3311,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.65092953,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"23","issue":"2","first_page":"203","last_page":"206"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.8766000270843506,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.8766000270843506,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.8629999756813049,"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/T10028","display_name":"Topic Modeling","score":0.8622000217437744,"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":0.7695710062980652},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.7175207138061523},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6278785467147827},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6011838912963867},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5477156639099121},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.49252280592918396},{"id":"https://openalex.org/keywords/cold-start","display_name":"Cold start (automotive)","score":0.4562992751598358},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.42258119583129883},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3765445649623871},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.33138635754585266},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.22932937741279602},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1019199788570404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7695710062980652},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.7175207138061523},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6278785467147827},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6011838912963867},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5477156639099121},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.49252280592918396},{"id":"https://openalex.org/C2778956030","wikidata":"https://www.wikidata.org/wiki/Q5142477","display_name":"Cold start (automotive)","level":2,"score":0.4562992751598358},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.42258119583129883},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3765445649623871},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.33138635754585266},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.22932937741279602},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1019199788570404},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lca.2024.3445948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lca.2024.3445948","pdf_url":null,"source":{"id":"https://openalex.org/S17643076","display_name":"IEEE Computer Architecture Letters","issn_l":"1556-6056","issn":["1556-6056","1556-6064","2473-2575"],"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 Computer Architecture Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2118231264","https://openalex.org/W2947737663","https://openalex.org/W3043023836","https://openalex.org/W3043433718","https://openalex.org/W3158146252","https://openalex.org/W3187188899","https://openalex.org/W3197720002","https://openalex.org/W3200211247","https://openalex.org/W6756363772","https://openalex.org/W6763737044"],"related_works":["https://openalex.org/W2529147798","https://openalex.org/W2081900870","https://openalex.org/W1979350723","https://openalex.org/W2528269032","https://openalex.org/W2964047085","https://openalex.org/W2555127516","https://openalex.org/W3180903918","https://openalex.org/W3000197790","https://openalex.org/W4285322112","https://openalex.org/W4292794239"],"abstract_inverted_index":{"Deep":[0],"learning":[1,11],"recommendation":[2],"model":[3],"(DLRM)":[4],"is":[5,44],"an":[6],"important":[7],"class":[8],"of":[9,88,102],"deep":[10],"networks":[12],"that":[13,106],"are":[14],"commonly":[15],"used":[16],"in":[17,60,82],"many":[18],"applications.":[19],"DRLM":[20],"presents":[21],"unique":[22],"challenges,":[23],"especially":[24],"for":[25],"scale-out":[26],"training":[27,111],"since":[28],"it":[29,107],"not":[30],"only":[31],"has":[32],"compute":[33],"and":[34],"memory-intensive":[35],"components":[36],"but":[37],"the":[38,41,47,86,89,95],"communication":[39],"between":[40],"multiple":[42],"GPUs":[43],"also":[45],"on":[46],"critical":[48],"path.":[49],"In":[50,71],"this":[51],"work,":[52],"we":[53],"propose":[54,68],"how":[55],"<italic":[56],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[57],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">cold</i>":[58],"data":[59],"DLRM":[61],"embedding":[62,74,76,96,104],"tables":[63],"can":[64,108],"be":[65,80],"exploited":[66],"to":[67,79,84],"proactive":[69,73,103],"embedding.":[70],"particular,":[72],"allows":[75],"table":[77],"accesses":[78],"done":[81],"advance":[83],"reduce":[85],"impact":[87],"memory":[90],"access":[91,97],"latency":[92],"by":[93,113],"overlapping":[94],"with":[98],"communication.":[99],"Our":[100],"analysis":[101],"demonstrates":[105],"improve":[109],"overall":[110],"performance":[112],"46%.":[114]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}