Orthogonal Random Forest for Causal Inference
Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu
Proceedings of the 36th International Conference on Machine Learning | September 2019
Papiers de Collaboration
Publications
Publication Type
-
Low-rank Bandit Methods for High-dimensional Dynamic Pricing
Jonas Mueller, Vasilis Syrgkanis, Matt Taddy
arXiv | September 2019
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments
Greg Lewis, Keith Battocchi, Maggie Hei, Miruna Oprescu, Vasilis Syrgkanis, Victor Lei
arXiv | May 2019
Semi-Parametric Efficient Policy Learning with Continuous Actions
Greg Lewis, Vasilis Syrgkanis, Victor Chernozhukov, Mert Demirer
arXiv | May 2019
Orthogonal Statistical Learning
Vasilis Syrgkanis, Dylan Foster
arXiv | March 2019
-
Semiparametric Contextual Bandits
Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis
International Conference on Machine Learning | July 2018
arXiv
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
Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation
Miruna Oprescu, Vasilis Syrgkanis, Steven Wu
June 2018
arXiv preprint arXiv:1806.03467
Adversarial Generalized Method of Moments
Greg Lewis, Vasilis Syrgkanis
March 2018
arXiv
-
Orthogonal Machine Learning: Power and Limitations
Lester Mackey, Vasilis Syrgkanis, Ilias Zadik
International Conference on Machine Learning | December 2017
Deep IV: A Flexible Approach for Counterfactual Prediction
Jason Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy
Proceedings of Machine Learning Research | August 2017
Filtre par zone de recherche
-
Orthogonal Statistical Learning
Vasilis Syrgkanis, Dylan Foster
arXiv | March 2019
-
Orthogonal Random Forest for Causal Inference
Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu
Proceedings of the 36th International Conference on Machine Learning | September 2019
Semiparametric Contextual Bandits
Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis
International Conference on Machine Learning | July 2018
arXiv
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
Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation
Miruna Oprescu, Vasilis Syrgkanis, Steven Wu
June 2018
arXiv preprint arXiv:1806.03467
-
Low-rank Bandit Methods for High-dimensional Dynamic Pricing
Jonas Mueller, Vasilis Syrgkanis, Matt Taddy
arXiv | September 2019
Semi-Parametric Efficient Policy Learning with Continuous Actions
Greg Lewis, Vasilis Syrgkanis, Victor Chernozhukov, Mert Demirer
arXiv | May 2019
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments
Greg Lewis, Keith Battocchi, Maggie Hei, Miruna Oprescu, Vasilis Syrgkanis, Victor Lei
arXiv | May 2019
Semiparametric Contextual Bandits
Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis
International Conference on Machine Learning | July 2018
arXiv
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
Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation
Miruna Oprescu, Vasilis Syrgkanis, Steven Wu
June 2018
arXiv preprint arXiv:1806.03467
Adversarial Generalized Method of Moments
Greg Lewis, Vasilis Syrgkanis
March 2018
arXiv
Orthogonal Machine Learning: Power and Limitations
Lester Mackey, Vasilis Syrgkanis, Ilias Zadik
International Conference on Machine Learning | December 2017
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 Type
-
Low-rank Bandit Methods for High-dimensional Dynamic Pricing
Jonas Mueller, Vasilis Syrgkanis, Matt Taddy
arXiv | September 2019
Semi-Parametric Efficient Policy Learning with Continuous Actions
Greg Lewis, Vasilis Syrgkanis, Victor Chernozhukov, Mert Demirer
arXiv | May 2019
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments
Greg Lewis, Keith Battocchi, Maggie Hei, Miruna Oprescu, Vasilis Syrgkanis, Victor Lei
arXiv | May 2019
Orthogonal Statistical Learning
Vasilis Syrgkanis, Dylan Foster
arXiv | March 2019
-
Orthogonal Random Forest for Causal Inference
Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu
Proceedings of the 36th International Conference on Machine Learning | September 2019
Semiparametric Contextual Bandits
Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis
International Conference on Machine Learning | July 2018
arXiv
Orthogonal Machine Learning: Power and Limitations
Lester Mackey, Vasilis Syrgkanis, Ilias Zadik
International Conference on Machine Learning | December 2017
Deep IV: A Flexible Approach for Counterfactual Prediction
Jason Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy
Proceedings of Machine Learning Research | August 2017
-
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
Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation
Miruna Oprescu, Vasilis Syrgkanis, Steven Wu
June 2018
arXiv preprint arXiv:1806.03467
-
Adversarial Generalized Method of Moments
Greg Lewis, Vasilis Syrgkanis
March 2018
arXiv