{"id":"https://openalex.org/W3093907268","doi":"https://doi.org/10.1145/3340531.3412704","title":"Ensembled CTR Prediction via Knowledge Distillation","display_name":"Ensembled CTR Prediction via Knowledge Distillation","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3093907268","doi":"https://doi.org/10.1145/3340531.3412704","mag":"3093907268"},"language":"en","primary_location":{"id":"doi:10.1145/3340531.3412704","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3412704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information &amp; Knowledge Management","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/A5048669373","display_name":"Jieming Zhu","orcid":"https://orcid.org/0000-0002-5666-8320"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jieming Zhu","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100705518","display_name":"Jinyang Liu","orcid":"https://orcid.org/0000-0003-0037-1912"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyang Liu","raw_affiliation_strings":["Sun Yat-Sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100651364","display_name":"Weiqi Li","orcid":"https://orcid.org/0000-0003-1218-0478"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiqi Li","raw_affiliation_strings":["Sun Yat-Sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037936136","display_name":"Jincai Lai","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jincai Lai","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083350101","display_name":"Xiuqiang He","orcid":"https://orcid.org/0000-0002-4115-8205"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuqiang He","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101957212","display_name":"Liang Chen","orcid":"https://orcid.org/0009-0006-1967-8075"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Chen","raw_affiliation_strings":["Sun Yat-Sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000582109","display_name":"Zibin Zheng","orcid":"https://orcid.org/0000-0002-7878-4330"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zibin Zheng","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2941","last_page":"2958"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9990000128746033,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7361652851104736},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7153810858726501},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6806000471115112},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.6494109630584717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6281321048736572},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.541957437992096},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4700022339820862},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.428022563457489},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.41825735569000244}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7361652851104736},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7153810858726501},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6806000471115112},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.6494109630584717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6281321048736572},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.541957437992096},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4700022339820862},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.428022563457489},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.41825735569000244},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3340531.3412704","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3412704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2076618162","https://openalex.org/W2475334473","https://openalex.org/W2509235963","https://openalex.org/W2512971201","https://openalex.org/W2593390416","https://openalex.org/W2604662567","https://openalex.org/W2610314927","https://openalex.org/W2723293840","https://openalex.org/W2793768763","https://openalex.org/W2898085636","https://openalex.org/W2903574258","https://openalex.org/W2911760887","https://openalex.org/W2946044191","https://openalex.org/W2947404296","https://openalex.org/W2948582784","https://openalex.org/W2950445386","https://openalex.org/W2963397674","https://openalex.org/W2963924287","https://openalex.org/W2964182926","https://openalex.org/W2979450518","https://openalex.org/W2997823717","https://openalex.org/W3096591391","https://openalex.org/W3098024612","https://openalex.org/W3101704389","https://openalex.org/W3104030692","https://openalex.org/W3104439459","https://openalex.org/W3104789011"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W3192840557","https://openalex.org/W4281381188","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W4375928479","https://openalex.org/W3131673289","https://openalex.org/W3198847674","https://openalex.org/W3096913503"],"abstract_inverted_index":{"Recently,":[0],"deep":[1],"learning-based":[2],"models":[3,169],"have":[4],"been":[5],"widely":[6],"studied":[7],"for":[8,136],"click-through":[9],"rate":[10],"(CTR)":[11],"prediction":[12,17],"and":[13,39,52,156,170,177],"lead":[14],"to":[15,33,80,88,99,125,148],"improved":[16],"accuracy":[18,113],"in":[19,56],"many":[20],"industrial":[21,173],"applications.":[22,58],"However,":[23],"current":[24],"research":[25],"focuses":[26],"primarily":[27],"on":[28,70],"building":[29],"complex":[30],"network":[31],"architectures":[32],"better":[34],"capture":[35],"sophisticated":[36],"feature":[37],"interactions":[38],"dynamic":[40],"user":[41],"behaviors.":[42],"The":[43,92,120],"increased":[44],"model":[45,66,87,103,108,140],"complexity":[46],"may":[47],"slow":[48],"down":[49],"online":[50,178],"inference":[51],"hinder":[53],"its":[54],"adoption":[55],"real-time":[57],"Instead,":[59],"our":[60,186],"work":[61],"targets":[62],"at":[63],"a":[64,76,85,89,105,131],"new":[65],"training":[67,188],"strategy":[68,94],"based":[69],"knowledge":[71,82],"distillation":[72,160],"(KD).":[73],"KD":[74,93],"is":[75],"teacher-student":[77],"learning":[78],"framework":[79],"transfer":[81],"learned":[83],"from":[84],"teacher":[86,118,154],"student":[90,102,139],"model.":[91],"not":[95],"only":[96],"allows":[97],"us":[98,124],"simplify":[100],"the":[101,116,128,183],"as":[104],"vanilla":[106],"DNN":[107],"but":[109],"also":[110,143],"achieves":[111],"significant":[112],"improvements":[114],"over":[115],"state-of-the-art":[117],"models.":[119],"benefits":[121],"thus":[122],"motivate":[123],"further":[126],"explore":[127],"use":[129],"of":[130,134,185],"powerful":[132],"ensemble":[133],"teachers":[135],"more":[137],"accurate":[138],"training.":[141],"We":[142,162],"propose":[144],"some":[145],"novel":[146],"techniques":[147],"facilitate":[149],"ensembled":[150],"CTR":[151],"prediction,":[152],"including":[153],"gating":[155],"early":[157],"stopping":[158],"by":[159],"loss.":[161],"conduct":[163],"comprehensive":[164],"experiments":[165],"against":[166],"12":[167],"existing":[168],"across":[171],"three":[172],"datasets.":[174],"Both":[175],"offline":[176],"A/B":[179],"testing":[180],"results":[181],"show":[182],"effectiveness":[184],"KD-based":[187],"strategy.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
