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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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Investigations of Performance and Bias in Human-AI Teamwork in Hiring


Feb 21, 2022
Andi Peng, Besmira Nushi, Emre Kiciman, Kori Inkpen, Ece Kamar

* Accepted at AAAI 2022 

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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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Invariant Language Modeling


Oct 16, 2021
Maxime Peyrard, Sarvjeet Singh Ghotra, Martin Josifoski, Vidhan Agarwal, Barun Patra, Dean Carignan, Emre Kiciman, Robert West


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Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix


Jan 16, 2021
Ruocheng Guo, Pengchuan Zhang, Hao Liu, Emre Kiciman

* 22 pages 

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Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions


Nov 11, 2020
Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman

* To be published in WSDM 

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DoWhy: An End-to-End Library for Causal Inference


Nov 09, 2020
Amit Sharma, Emre Kiciman

* 5 pages 

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Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction


Oct 17, 2020
Shuxi Zeng, Murat Ali Bayir, Joel Pfeiffer, Denis Charles, Emre Kiciman

* 9 pages, 8 figures, 2 tables, accepted to WSDM 2021 

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Security and Machine Learning in the Real World


Jul 13, 2020
Ivan Evtimov, Weidong Cui, Ece Kamar, Emre Kiciman, Tadayoshi Kohno, Jerry Li


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AvE: Assistance via Empowerment


Jul 09, 2020
Yuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani, Pieter Abbeel, Anca Dragan

* Fix missing citation on page 4; edit acknowledgements 

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