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Knowledge Distillation as Semiparametric Inference


Apr 20, 2021
Tri Dao, Govinda M Kamath, Vasilis Syrgkanis, Lester Mackey


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Estimating the Long-Term Effects of Novel Treatments


Mar 15, 2021
Keith Battocchi, Eleanor Dillon, Maggie Hei, Greg Lewis, Miruna Oprescu, Vasilis Syrgkanis


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Evidence-Based Policy Learning


Mar 12, 2021
Jann Spiess, Vasilis Syrgkanis


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Adversarial Estimation of Riesz Representers


Dec 30, 2020
Victor Chernozhukov, Whitney Newey, Rahul Singh, Vasilis Syrgkanis


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Asymptotics of the Empirical Bootstrap Method Beyond Asymptotic Normality


Nov 23, 2020
Morgane Austern, Vasilis Syrgkanis


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Bid Prediction in Repeated Auctions with Learning


Jul 26, 2020
Gali Noti, Vasilis Syrgkanis


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Minimax Estimation of Conditional Moment Models


Jun 12, 2020
Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis


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Double/Debiased Machine Learning for Dynamic Treatment Effects


Feb 17, 2020
Greg Lewis, Vasilis Syrgkanis


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Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments


Jun 06, 2019
Vasilis Syrgkanis, Victor Lei, Miruna Oprescu, Maggie Hei, Keith Battocchi, Greg Lewis


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Semi-Parametric Efficient Policy Learning with Continuous Actions


May 24, 2019
Mert Demirer, Vasilis Syrgkanis, Greg Lewis, Victor Chernozhukov


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Orthogonal Statistical Learning


Jan 25, 2019
Dylan J. Foster, Vasilis Syrgkanis


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Non-Parametric Inference Adaptive to Intrinsic Dimension


Jan 11, 2019
Khashayar Khosravi, Greg Lewis, Vasilis Syrgkanis


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Orthogonal Machine Learning: Power and Limitations


Aug 01, 2018
Lester Mackey, Vasilis Syrgkanis, Ilias Zadik


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Semiparametric Contextual Bandits


Jul 16, 2018
Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis


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Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation


Jul 12, 2018
Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu


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Bayesian Exploration: Incentivizing Exploration in Bayesian Games


Jul 01, 2018
Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis, Zhiwei Steven Wu


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


Jun 30, 2018
Victor Chernozhukov, Denis Nekipelov, Vira Semenova, Vasilis Syrgkanis


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Accurate Inference for Adaptive Linear Models


Jun 20, 2018
Yash Deshpande, Lester Mackey, Vasilis Syrgkanis, Matt Taddy

* 20 pages; Updated after acceptance to ICML 2018 

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Learning to Bid Without Knowing your Value


Jun 01, 2018
Zhe Feng, Chara Podimata, Vasilis Syrgkanis

* In the Proceedings of the 19th ACM Conference on Economics and Computation, 2018 (to appear) 

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Optimal and Myopic Information Acquisition


May 14, 2018
Annie Liang, Xiaosheng Mu, Vasilis Syrgkanis


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Adversarial Generalized Method of Moments


Apr 24, 2018
Greg Lewis, Vasilis Syrgkanis


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Inference on Auctions with Weak Assumptions on Information


Mar 19, 2018
Vasilis Syrgkanis, Elie Tamer, Juba Ziani


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Expert identification of visual primitives used by CNNs during mammogram classification


Mar 13, 2018
Jimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester Mackey, Genevieve Patterson

* Medical Imaging 2018: Computer-Aided Diagnosis, Proc. of SPIE Vol. 10575, 105752T 

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Training GANs with Optimism


Feb 13, 2018
Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis, Haoyang Zeng


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Low-rank Bandit Methods for High-dimensional Dynamic Pricing


Jan 30, 2018
Jonas Mueller, Vasilis Syrgkanis, Matt Taddy


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Robust Optimization for Non-Convex Objectives


Jul 04, 2017
Robert Chen, Brendan Lucier, Yaron Singer, Vasilis Syrgkanis


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A Proof of Orthogonal Double Machine Learning with $Z$-Estimators


Apr 14, 2017
Vasilis Syrgkanis


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Oracle-Efficient Online Learning and Auction Design


Apr 13, 2017
Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan


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A Sample Complexity Measure with Applications to Learning Optimal Auctions


Apr 11, 2017
Vasilis Syrgkanis


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