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Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud


Sep 07, 2021
Michaela Hardt, Xiaoguang Chen, Xiaoyi Cheng, Michele Donini, Jason Gelman, Satish Gollaprolu, John He, Pedro Larroy, Xinyu Liu, Nick McCarthy, Ashish Rathi, Scott Rees, Ankit Siva, ErhYuan Tsai, Keerthan Vasist, Pinar Yilmaz, Muhammad Bilal Zafar, Sanjiv Das, Kevin Haas, Tyler Hill, Krishnaram Kenthapadi

* In Proc. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2974-2983 (2021) 

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Linear Dynamics: Clustering without identification


Sep 02, 2019
Chloe Ching-Yun Hsu, Michaela Hardt, Moritz Hardt


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Explaining an increase in predicted risk for clinical alerts


Jul 10, 2019
Michaela Hardt, Alvin Rajkomar, Gerardo Flores, Andrew Dai, Michael Howell, Greg Corrado, Claire Cui, Moritz Hardt


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Scalable and accurate deep learning for electronic health records


May 11, 2018
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Peter J. Liu, Xiaobing Liu, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Gavin E. Duggan, Gerardo Flores, Michaela Hardt, Jamie Irvine, Quoc Le, Kurt Litsch, Jake Marcus, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael Howell, Claire Cui, Greg Corrado, Jeff Dean

* npj Digital Medicine 1:18 (2018) 
* Published version from https://www.nature.com/articles/s41746-018-0029-1 

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