EconML

A Causal AI Suite for Decision-Making

Emre Kiciman, Eleanor Dillon, Darren Edge, Adam Foster, Agrin Hilmkil, Joel Jennings, Chao Ma, Robert Osazuwa Ness, Nick Pawlowski, Amit Sharma, Cheng Zhang

NeurIPS 2022 Workshop on Causality for Real-world Impact | December 2022

Publication Project Project

Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber

Vasilis Syrgkanis, Greg Lewis, Miruna Oprescu, Maggie Hei, Keith Battocchi, Eleanor Dillon, Jing Pan, Yifeng Wu, Paul Lo, Huigang Chen, Totte Harinen, Jeong-Yoon Lee

2021 Knowledge Discovery and Data Mining | September 2021

Publication

Orthogonal Random Forest for Causal Inference

Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu

Proceedings of the 36th International Conference on Machine Learning | September 2019

Publication Project

Low-rank Bandit Methods for High-dimensional Dynamic Pricing

Jonas Mueller, Vasilis Syrgkanis, Matt Taddy

arXiv | September 2019

Publication Project

Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments

Greg Lewis, Keith Battocchi, Maggie Hei, Miruna Oprescu, Vasilis Syrgkanis, Victor Lei

arXiv | May 2019

Publication Project

Semi-Parametric Efficient Policy Learning with Continuous Actions

Greg Lewis, Vasilis Syrgkanis, Victor Chernozhukov, Mert Demirer

arXiv | May 2019

Publication Project

Orthogonal Statistical Learning

Vasilis Syrgkanis, Dylan Foster

arXiv | March 2019

Publication Project

Semiparametric Contextual Bandits

Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis

International Conference on Machine Learning | July 2018

arXiv

Publication Project

Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models

Victor Chernozhukov, Denis Nekipelov, Vira Semenova, Vasilis Syrgkanis

June 2018

arXiv preprint arXiv:1806.04823

Publication Project

Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation

Miruna Oprescu, Vasilis Syrgkanis, Steven Wu

June 2018

arXiv preprint arXiv:1806.03467

Publication Project

Adversarial Generalized Method of Moments

Greg Lewis, Vasilis Syrgkanis

March 2018

arXiv

Publication Project

Orthogonal Machine Learning: Power and Limitations

Lester Mackey, Vasilis Syrgkanis, Ilias Zadik

International Conference on Machine Learning | December 2017

Publication Project

Deep IV: A Flexible Approach for Counterfactual Prediction

Jason Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy

Proceedings of Machine Learning Research | August 2017

Publication Project

A Causal AI Suite for Decision-Making

Emre Kiciman, Eleanor Dillon, Darren Edge, Adam Foster, Agrin Hilmkil, Joel Jennings, Chao Ma, Robert Osazuwa Ness, Nick Pawlowski, Amit Sharma, Cheng Zhang

NeurIPS 2022 Workshop on Causality for Real-world Impact | December 2022

Publication Project Project

Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber

Vasilis Syrgkanis, Greg Lewis, Miruna Oprescu, Maggie Hei, Keith Battocchi, Eleanor Dillon, Jing Pan, Yifeng Wu, Paul Lo, Huigang Chen, Totte Harinen, Jeong-Yoon Lee

2021 Knowledge Discovery and Data Mining | September 2021

Publication

Orthogonal Random Forest for Causal Inference

Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu

Proceedings of the 36th International Conference on Machine Learning | September 2019

Publication Project

Semiparametric Contextual Bandits

Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis

International Conference on Machine Learning | July 2018

arXiv

Publication Project

Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models

Victor Chernozhukov, Denis Nekipelov, Vira Semenova, Vasilis Syrgkanis

June 2018

arXiv preprint arXiv:1806.04823

Publication Project

Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation

Miruna Oprescu, Vasilis Syrgkanis, Steven Wu

June 2018

arXiv preprint arXiv:1806.03467

Publication Project

Orthogonal Statistical Learning

Vasilis Syrgkanis, Dylan Foster

arXiv | March 2019

Publication Project

Low-rank Bandit Methods for High-dimensional Dynamic Pricing

Jonas Mueller, Vasilis Syrgkanis, Matt Taddy

arXiv | September 2019

Publication Project

Semi-Parametric Efficient Policy Learning with Continuous Actions

Greg Lewis, Vasilis Syrgkanis, Victor Chernozhukov, Mert Demirer

arXiv | May 2019

Publication Project

Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments

Greg Lewis, Keith Battocchi, Maggie Hei, Miruna Oprescu, Vasilis Syrgkanis, Victor Lei

arXiv | May 2019

Publication Project

Semiparametric Contextual Bandits

Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis

International Conference on Machine Learning | July 2018

arXiv

Publication Project

Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models

Victor Chernozhukov, Denis Nekipelov, Vira Semenova, Vasilis Syrgkanis

June 2018

arXiv preprint arXiv:1806.04823

Publication Project

Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation

Miruna Oprescu, Vasilis Syrgkanis, Steven Wu

June 2018

arXiv preprint arXiv:1806.03467

Publication Project

Adversarial Generalized Method of Moments

Greg Lewis, Vasilis Syrgkanis

March 2018

arXiv

Publication Project

Orthogonal Machine Learning: Power and Limitations

Lester Mackey, Vasilis Syrgkanis, Ilias Zadik

International Conference on Machine Learning | December 2017

Publication Project

Deep IV: A Flexible Approach for Counterfactual Prediction

Jason Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy

Proceedings of Machine Learning Research | August 2017

Publication Project

A Causal AI Suite for Decision-Making

Emre Kiciman, Eleanor Dillon, Darren Edge, Adam Foster, Agrin Hilmkil, Joel Jennings, Chao Ma, Robert Osazuwa Ness, Nick Pawlowski, Amit Sharma, Cheng Zhang

NeurIPS 2022 Workshop on Causality for Real-world Impact | December 2022

Publication Project Project

Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber

Vasilis Syrgkanis, Greg Lewis, Miruna Oprescu, Maggie Hei, Keith Battocchi, Eleanor Dillon, Jing Pan, Yifeng Wu, Paul Lo, Huigang Chen, Totte Harinen, Jeong-Yoon Lee

2021 Knowledge Discovery and Data Mining | September 2021

Publication

Orthogonal Random Forest for Causal Inference

Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu

Proceedings of the 36th International Conference on Machine Learning | September 2019

Publication Project

Semiparametric Contextual Bandits

Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis

International Conference on Machine Learning | July 2018

arXiv

Publication Project

Orthogonal Machine Learning: Power and Limitations

Lester Mackey, Vasilis Syrgkanis, Ilias Zadik

International Conference on Machine Learning | December 2017

Publication Project

Deep IV: A Flexible Approach for Counterfactual Prediction

Jason Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy

Proceedings of Machine Learning Research | August 2017

Publication Project

Low-rank Bandit Methods for High-dimensional Dynamic Pricing

Jonas Mueller, Vasilis Syrgkanis, Matt Taddy

arXiv | September 2019

Publication Project

Semi-Parametric Efficient Policy Learning with Continuous Actions

Greg Lewis, Vasilis Syrgkanis, Victor Chernozhukov, Mert Demirer

arXiv | May 2019

Publication Project

Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments

Greg Lewis, Keith Battocchi, Maggie Hei, Miruna Oprescu, Vasilis Syrgkanis, Victor Lei

arXiv | May 2019

Publication Project

Orthogonal Statistical Learning

Vasilis Syrgkanis, Dylan Foster

arXiv | March 2019

Publication Project

Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models

Victor Chernozhukov, Denis Nekipelov, Vira Semenova, Vasilis Syrgkanis

June 2018

arXiv preprint arXiv:1806.04823

Publication Project

Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation

Miruna Oprescu, Vasilis Syrgkanis, Steven Wu

June 2018

arXiv preprint arXiv:1806.03467

Publication Project

Adversarial Generalized Method of Moments

Greg Lewis, Vasilis Syrgkanis

March 2018

arXiv

Publication Project