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Recursive Partitioning for Heterogeneous Causal Effects

5 April 2015

Papers citing "Recursive Partitioning for Heterogeneous Causal Effects"

50 / 188 papers shown

Title
Explanatory causal effects for model agnostic explanations Jiuyong Li Ha Xuan Tran T. Le Lin Liu Kui Yu Jixue Liu CML 70 1 0 23 Jun 2022
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work? Susanne Dandl Torsten Hothorn H. Seibold Erik Sverdrup Stefan Wager A. Zeileis CML 71 11 0 21 Jun 2022
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability Jonathan Crabbé Alicia Curth Ioana Bica M. Schaar CML 110 16 0 16 Jun 2022
Learning Disentangled Representations for Counterfactual Regression via Mutual Information Minimization Min Cheng Xinru Liao Quanlian Liu Bin Ma Jian Xu Bo Zheng CML 69 25 0 02 Jun 2022
Robust and Agnostic Learning of Conditional Distributional Treatment Effects Nathan Kallus Miruna Oprescu OOD CML 122 12 0 23 May 2022
What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment Nathan Kallus 76 23 0 20 May 2022
The Fairness of Credit Scoring Models Christophe Hurlin C. Pérignon Sébastien Saurin FaML 62 25 0 20 May 2022
Multi-disciplinary fairness considerations in machine learning for clinical trials Isabel Chien Nina Deliu Richard Turner Adrian Weller S. Villar Niki Kilbertus FaML 71 23 0 18 May 2022
Searching for subgroup-specific associations while controlling the false discovery rate M. Sesia Tianshu Sun 85 0 0 17 May 2022
Multiple Domain Causal Networks Tianhui Zhou IV WilliamE.Carson M. H. Klein David Carlson CML 37 0 0 13 May 2022
Learning Optimal Dynamic Treatment Regimes Using Causal Tree Methods in Medicine Theresa Blümlein Joel Persson Stefan Feuerriegel CML 65 13 0 14 Apr 2022
Calibration Error for Heterogeneous Treatment Effects Yizhe Xu Steve Yadlowsky 59 12 0 24 Mar 2022
Minimax rates for heterogeneous causal effect estimation Edward H. Kennedy Sivaraman Balakrishnan James M. Robins Larry A. Wasserman CML 93 31 0 02 Mar 2022
Estimating causal effects with optimization-based methods: A review and empirical comparison Martin Cousineau V. Verter Susan Murphy J. Pineau CML 40 9 0 28 Feb 2022
Differentially Private Estimation of Heterogeneous Causal Effects Fengshi Niu Harsha Nori B. Quistorff R. Caruana Donald Ngwe A. Kannan CML 93 14 0 22 Feb 2022
Generalized Causal Tree for Uplift Modeling Preetam Nandy Xiufan Yu Wanjun Liu Ye Tu Kinjal Basu S. Chatterjee CML 72 4 0 04 Feb 2022
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods Abhineet Agarwal Yan Shuo Tan Omer Ronen Chandan Singh Bin Yu 90 27 0 02 Feb 2022
Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance Gabriel Okasa CML 51 6 0 30 Jan 2022
Heterogeneous Peer Effects in the Linear Threshold Model Christopher Tran Elena Zheleva 96 13 0 27 Jan 2022
Meta-Analysis of Randomized Experiments with Applications to Heavy-Tailed Response Data Nilesh Tripuraneni Dhruv Madeka Dean Phillips Foster Dominique C. Perrault-Joncas Michael I. Jordan 69 5 0 14 Dec 2021
Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation Ramtin Keramati Omer Gottesman Leo Anthony Celi Finale Doshi-Velez Emma Brunskill OffRL 21 6 0 28 Nov 2021
A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling Eustache Diemert Artem Betlei Christophe Renaudin Massih-Reza Amini T. Gregoir Thibaud Rahier CML 71 10 0 19 Nov 2021
An Online Sequential Test for Qualitative Treatment Effects C. Shi Shuang Luo Hong-Tu Zhu Rui Song 86 3 0 06 Nov 2021
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
Mixed-Integer Optimization with Constraint Learning Donato Maragno H. Wiberg Dimitris Bertsimas Ş. Birbil D. Hertog Adejuyigbe O. Fajemisin 108 55 0 04 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
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Alicia Curth Changhee Lee M. Schaar CML 77 30 0 26 Oct 2021
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds Yan Shuo Tan Abhineet Agarwal Bin Yu 79 11 0 18 Oct 2021
Estimating Potential Outcome Distributions with Collaborating Causal Networks Tianhui Zhou William E Carson IV David Carlson CML 217 8 0 04 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
Machine learning reveals how personalized climate communication can both succeed and backfire Totte Harinen Alex Filipowicz Shabnam Hakimi Rumen Iliev M. Klenk Emily S. Sumner AI4CE 51 5 0 10 Sep 2021
The Role of "Live" in Livestreaming Markets: Evidence Using Orthogonal Random Forest Ziwei Cong Jia Liu Puneet Manchanda 27 7 0 04 Jul 2021
Tree-Values: selective inference for regression trees Anna Neufeld Lucy L. Gao Daniela Witten 62 26 0 15 Jun 2021
Learning Treatment Effects in Panels with General Intervention Patterns Vivek F. Farias Andrew A. Li Tianyi Peng CML 78 10 0 05 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
Markdowns in E-Commerce Fresh Retail: A Counterfactual Prediction and Multi-Period Optimization Approach Junhao Hua Ling Yan Huan Xu Cheng Yang 41 17 0 18 May 2021
Business analytics meets artificial intelligence: Assessing the demand effects of discounts on Swiss train tickets M. Huber Jonas Meier H. Wallimann CML 38 19 0 04 May 2021
What can the millions of random treatments in nonexperimental data reveal about causes? Andre F. Ribeiro Frank Neffke Ricardo Hausmann CML 49 1 0 03 May 2021
Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters Carlos Fernández-Loría F. Provost CML 67 45 0 08 Apr 2021
Robust Orthogonal Machine Learning of Treatment Effects Yiyan Huang Cheuk Hang Leung Qi Wu Xing Yan OOD CML 57 0 0 22 Mar 2021
A Review of Generalizability and Transportability Irina Degtiar Sherri Rose CML 53 220 0 23 Feb 2021
Shrinkage Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation A. Caron G. Baio I. Manolopoulou CML 84 16 0 12 Feb 2021
Invariant Representation Learning for Treatment Effect Estimation Claudia Shi Victor Veitch David M. Blei OOD CML 57 31 0 24 Nov 2020
Targeting for long-term outcomes Jeremy Yang Dean Eckles Paramveer S. Dhillon Sinan Aral OffRL 65 52 0 29 Oct 2020
Interpretable Assessment of Fairness During Model Evaluation A. Sepehri Cyrus DiCiccio FaML 13 1 0 26 Oct 2020
Survey on Causal-based Machine Learning Fairness Notions K. Makhlouf Sami Zhioua C. Palamidessi FaML 151 85 0 19 Oct 2020
Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction Shuxi Zeng Murat Ali Bayir Joel Pfeiffer Denis Xavier Charles Emre Kıcıman TTA 48 18 0 17 Oct 2020
Targeted VAE: Variational and Targeted Learning for Causal Inference M. Vowels Necati Cihan Camgöz Richard Bowden BDL OOD CML 47 8 0 28 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
Sufficient Dimension Reduction for Average Causal Effect Estimation Debo Cheng Jiuyong Li Lin Liu Jixue Liu CML 51 15 0 14 Sep 2020