基于深度学习多实验叠加效果因果推断.pdf

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1、DataFunDataFun SummitSummit#20232023基于深度学习多实验因果推断基于深度学习多实验因果推断张任宇张任宇快手经济学家快手经济学家香港香港中文大学副教授中文大学副教授OctOct 21,21,20232023张任宇 Philip Zhang三位一体数据科学家/运营管理学青椒:学者+老师+互联网搬砖工快手经济学家（2018-）香港中文大学商学院(tenured)副教授（2021-）；研究数据科学在互联网平台策略评估与优化的应用；面向本科、硕士、PhD和EMBA讲授数据科学在商业的应用。2上海纽约大学助理教授（2016-2022）圣路易斯华盛顿大学运营管理学博士（20

2、11-2016）北京大学数学本科（2007-2011）我是谁我是谁？DeepDeep LearningLearning MeetsMeets DoubleDouble MachineMachine Learning:Learning:CausalCausal InferenceInference forfor Large-ScaleLarge-Scale CombinatorialCombinatorial ExperimentsExperimentsRenyu(Philip)ZhangKuaishou Economist Team and CUHK Business School(Based

3、 on the join work with Zikun Ye,Zhiqi Zhang,Dennis Zhang,Heng Zhang)OutlineOutline ofof thethe TalkTalkIntroduction:Problem,Solution and ContributionsTheory:Debiased Deep Learning and AsymptoticsEmpirics:Validations with Field Experiment Data4Number of Experiments per week5Exp 1:Get Rewards StickerL

4、aunch Two Experiments to increase watching timeExp 2:Send Gift StickerMultipleMultiple A/BA/B TestsTests6MultipleMultiple A/BA/B TestsTestsExp 1Exp 2Exp 1+Exp 2Control7 Major Question:How to estimate and infer the combined treatment effect ofmultiple A/B tests?MultipleMultiple A/BA/B TestsTests8Solu

5、tionSolution 1:1:LinearLinear AdditionAdditionEffect of(Exp 1+Exp 2)=Effect of Exp 1+Effect of Exp 2 Limitations:Non-linearity of treatment effects:o Marginal Decreasing:negative interactiono Marginal Increasing:positive interactionControlExp 1Exp 2No ButtonReward StickerGift Sticker9SolutionSolutio

6、n 2:2:FullFull FactorialFactorial DesignDesignRun All treatment combinationsLimitations:Exponentially Large treatment combinations:o binary-level tests generate 2 combinationso Impossible to assign even 1 user to each combination if 30ControlExp 1Exp 2Exp 1+Exp 2No StickerReward StickerGift StickerB