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Quasi-Oracle Estimation of Heterogeneous Treatment Effects

13 December 2017

Papers citing "Quasi-Oracle Estimation of Heterogeneous Treatment Effects"

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Title
Interpretable Personalized Experimentation Han Wu S. Tan Weiwei Li Mia Garrard Adam Obeng Drew Dimmery Shaun Singh Hanson Wang Daniel R. Jiang E. Bakshy 65 6 0 05 Nov 2021
Heterogeneous Effects of Software Patches in a Multiplayer Online Battle Arena Game Yuzi He Christopher Tran Julie Jiang Keith Burghardt Emilio Ferrara Elena Zheleva Kristina Lerman 45 10 0 27 Oct 2021
Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance Justin Lim Christina X. Ji Michael Oberst S. Blecker Leora I. Horwitz David Sontag CML 50 5 0 27 Oct 2021
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection Chunjong Park Anas Awadalla Tadayoshi Kohno Shwetak N. Patel OOD 65 30 0 26 Oct 2021
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Alicia Curth Changhee Lee M. Schaar CML 77 30 0 26 Oct 2021
Heterogeneous Treatment Effect Estimation using machine learning for Healthcare application: tutorial and benchmark Yaobin Ling Pulakesh Upadhyaya Luyao Chen Xiaoqian Jiang Yejin Kim CML 167 21 0 27 Sep 2021
Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment Eli Ben-Michael D. J. Greiner Kosuke Imai Zhichao Jiang OffRL 229 22 0 22 Sep 2021
DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions Amit Sharma Vasilis Syrgkanis Cheng Zhang Emre Kıcıman 78 26 0 27 Aug 2021
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects Yao Zhang Jeroen Berrevoets M. Schaar CML 84 6 0 06 Aug 2021
Doing Great at Estimating CATE? On the Neglected Assumptions in Benchmark Comparisons of Treatment Effect Estimators Alicia Curth M. Schaar CML 49 7 0 28 Jul 2021
CausalNLP: A Practical Toolkit for Causal Inference with Text Arun S. Maiya CML 44 3 0 15 Jun 2021
Machine Learning for Variance Reduction in Online Experiments Yongyi Guo Dominic Coey Mikael Konutgan Wenting Li Ch. P. Schoener Matt Goldman 59 35 0 14 Jun 2021
On Inductive Biases for Heterogeneous Treatment Effect Estimation Alicia Curth M. Schaar CML 193 84 0 07 Jun 2021
Causal Effect Inference for Structured Treatments Jean Kaddour Yuchen Zhu Qi Liu Matt J. Kusner Ricardo M. A. Silva CML 262 51 0 03 Jun 2021
Adaptive Multi-Source Causal Inference Thanh Vinh Vo Pengfei Wei T. Hoang Tze-Yun Leong 92 1 0 31 May 2021
Federated Estimation of Causal Effects from Observational Data Thanh Vinh Vo T. Hoang Young Lee Tze-Yun Leong FedML CML 70 13 0 31 May 2021
A Twin Neural Model for Uplift Mouloud Belbahri Olivier Gandouet A. Murua V. Nia CML 13 1 0 11 May 2021
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference AmirEmad Ghassami Andrew Ying I. Shpitser E. T. Tchetgen 90 44 0 07 Apr 2021
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources Xiaoqing Ellen Tan Chung Chang Ling Zhou Lu Tang CML 73 18 0 10 Mar 2021
Median Optimal Treatment Regimes Liu Leqi Edward H. Kennedy 102 8 0 02 Mar 2021
Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension Rahul Singh CML 91 8 0 22 Feb 2021
Shrinkage Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation A. Caron G. Baio I. Manolopoulou CML 84 16 0 12 Feb 2021
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms Alicia Curth M. Schaar CML 181 149 0 26 Jan 2021
Estimating Average Treatment Effects via Orthogonal Regularization Tobias Hatt Stefan Feuerriegel CML 239 36 0 21 Jan 2021
Kernel Methods for Unobserved Confounding: Negative Controls, Proxies, and Instruments Rahul Singh CML 98 41 0 18 Dec 2020
Treatment Targeting by AUUC Maximization with Generalization Guarantees Artem Betlei Eustache Diemert Massih-Reza Amini CML 65 5 0 17 Dec 2020
Rejoinder: New Objectives for Policy Learning Nathan Kallus 74 1 0 05 Dec 2020
Deep Learning for Individual Heterogeneity M. Farrell Tengyuan Liang S. Misra BDL 74 17 0 28 Oct 2020
Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves Rahul Singh Liyuan Xu Arthur Gretton OffRL 144 31 0 10 Oct 2020
Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects Falco J. Bargagli-Stoffi Riccardo Cadei Kwonsang Lee Francesca Dominici CML 58 16 0 18 Sep 2020
Estimating Individual Treatment Effects using Non-Parametric Regression Models: a Review A. Caron G. Baio I. Manolopoulou CML 109 56 0 14 Sep 2020
Stable discovery of interpretable subgroups via calibration in causal studies Raaz Dwivedi Yan Shuo Tan Briton Park Mian Wei Kevin Horgan D. Madigan Bin Yu CML 54 30 0 23 Aug 2020
Estimating Structural Target Functions using Machine Learning and Influence Functions Alicia Curth Ahmed Alaa M. Schaar CML TDI 82 3 0 14 Aug 2020
A unified survey of treatment effect heterogeneity modeling and uplift modeling Weijia Zhang Jiuyong Li Lin Liu CML 97 60 0 14 Jul 2020
Design and Evaluation of Personalized Free Trials Hema Yoganarasimhan E. Barzegary Abhishek Pani 45 12 0 24 Jun 2020
Assumption-lean inference for generalised linear model parameters S. Vansteelandt O. Dukes CML 150 54 0 15 Jun 2020
Conformal Inference of Counterfactuals and Individual Treatment Effects Lihua Lei Emmanuel J. Candès CML 174 195 0 11 Jun 2020
Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects Qiming Du Gérard Biau Franccois Petit R. Porcher CML BDL 68 6 0 08 Jun 2020
Learning Joint Nonlinear Effects from Single-variable Interventions in the Presence of Hidden Confounders Sorawit Saengkyongam Ricardo M. A. Silva CML 33 10 0 23 May 2020
Feature Selection Methods for Uplift Modeling and Heterogeneous Treatment Effect Zhenyu Zhao Yumin Zhang Totte Harinen Mike Yung CML 16 2 0 05 May 2020
Towards optimal doubly robust estimation of heterogeneous causal effects Edward H. Kennedy CML 196 328 0 29 Apr 2020
A Comparison of Methods for Treatment Assignment with an Application to Playlist Generation Carlos Fernández-Loría F. Provost J. Anderton Benjamin Carterette Praveen Chandar CML 74 19 0 24 Apr 2020
Learning Continuous Treatment Policy and Bipartite Embeddings for Matching with Heterogeneous Causal Effects Will Y. Zou S. Shyam Michael Mui Mingshi Wang Jan Pedersen Zoubin Ghahramani CML 53 2 0 21 Apr 2020
Heterogeneous Causal Learning for Effectiveness Optimization in User Marketing Will Y. Zou Shuyang Du James Lee Jan Pedersen CML 26 7 0 21 Apr 2020
Adversarial Validation Approach to Concept Drift Problem in User Targeting Automation Systems at Uber Jing Pan Vincent Pham Mohan Dorairaj Huigang Chen Jeong-Yoon Lee AAML 8 7 0 07 Apr 2020
CausalML: Python Package for Causal Machine Learning Huigang Chen Totte Harinen Jeong-Yoon Lee Mike Yung Zhenyu Zhao CML 71 114 0 25 Feb 2020
Double/Debiased Machine Learning for Dynamic Treatment Effects via g-Estimation Greg Lewis Vasilis Syrgkanis CML 76 35 0 17 Feb 2020
Minimax Optimal Nonparametric Estimation of Heterogeneous Treatment Effects Zijun Gao Yanjun Han CML 87 16 0 15 Feb 2020
A Survey on Causal Inference Liuyi Yao Zhixuan Chu Sheng Li Yaliang Li Jing Gao Aidong Zhang CML 123 516 0 05 Feb 2020
Estimating heterogeneous treatment effects with right-censored data via causal survival forests Yifan Cui Michael R. Kosorok Erik Sverdrup Stefan Wager Ruoqing Zhu CML 74 75 0 27 Jan 2020