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Population-Based Black-Box Optimization for Biological Sequence Design


Jun 05, 2020
Christof Angermueller, David Belanger, Andreea Gane, Zelda Mariet, David Dohan, Kevin Murphy, Lucy Colwell, D Sculley


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Fair treatment allocations in social networks


Nov 01, 2019
James Atwood, Hansa Srinivasan, Yoni Halpern, D Sculley

* To appear in the Fair ML for Health workshop at NeurIPS 2019 

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Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift


Jun 06, 2019
Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, D Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek


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Avoiding a Tragedy of the Commons in the Peer Review Process


Dec 18, 2018
D Sculley, Jasper Snoek, Alex Wiltschko

* Appeared in the 2018 Advances in Neural Information Processing Systems Workshop on Critiquing and Correcting Trends in Machine Learning 

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AutoGraph: Imperative-style Coding with Graph-based Performance


Oct 16, 2018
Dan Moldovan, James M Decker, Fei Wang, Andrew A Johnson, Brian K Lee, Zachary Nado, D Sculley, Tiark Rompf, Alexander B Wiltschko


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TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks


Aug 08, 2017
Heng-Tze Cheng, Zakaria Haque, Lichan Hong, Mustafa Ispir, Clemens Mewald, Illia Polosukhin, Georgios Roumpos, D Sculley, Jamie Smith, David Soergel, Yuan Tang, Philipp Tucker, Martin Wicke, Cassandra Xia, Jianwei Xie

* 8 pages, Appeared at KDD 2017, August 13--17, 2017, Halifax, NS, Canada 

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