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The Counterfactual-Shapley Value: Attributing Change in System Metrics


Aug 17, 2022
Amit Sharma, Hua Li, Jian Jiao


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Probing Classifiers are Unreliable for Concept Removal and Detection


Jul 08, 2022
Abhinav Kumar, Chenhao Tan, Amit Sharma


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Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization


Jun 15, 2022
Jivat Neet Kaur, Emre Kiciman, Amit Sharma


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Machine Explanations and Human Understanding


Feb 08, 2022
Chacha Chen, Shi Feng, Amit Sharma, Chenhao Tan

* 26 pages, 13 figures 

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Deep End-to-end Causal Inference


Feb 04, 2022
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang


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Omitted Variable Bias in Machine Learned Causal Models


Dec 29, 2021
Victor Chernozhukov, Carlos Cinelli, Whitney Newey, Amit Sharma, Vasilis Syrgkanis

* This version of the paper was prepared for the NeurIPS-2021 Workshop "Causal Inference & Machine Learning: Why now?''; 32 pages; 4 figures; typos corrected 

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Causal Regularization Using Domain Priors


Nov 24, 2021
Abbavaram Gowtham Reddy, Sai Srinivas Kancheti, Vineeth N Balasubramanian, Amit Sharma


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Sayer: Using Implicit Feedback to Optimize System Policies


Oct 28, 2021
Mathias Lécuyer, Sang Hoon Kim, Mihir Nanavati, Junchen Jiang, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins


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The Connection between Out-of-Distribution Generalization and Privacy of ML Models


Oct 07, 2021
Divyat Mahajan, Shruti Tople, Amit Sharma

* Prior version accepted at Workshop on Privacy Preserving Machine Learning, NeurIPS 2020. Code: https://github.com/microsoft/robustdg 

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