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Underspecification Presents Challenges for Credibility in Modern Machine Learning

Nov 06, 2020
Alexander D'Amour, Katherine Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yian Ma, Cory McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley


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Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift

Jul 17, 2020
Zachary Nado, Shreyas Padhy, D. Sculley, Alexander D'Amour, Balaji Lakshminarayanan, Jasper Snoek


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TensorFlow.js: Machine Learning for the Web and Beyond

Jan 16, 2019
Daniel Smilkov, Nikhil Thorat, Yannick Assogba, Ann Yuan, Nick Kreeger, Ping Yu, Kangyi Zhang, Shanqing Cai, Eric Nielsen, David Soergel, Stan Bileschi, Michael Terry, Charles Nicholson, Sandeep N. Gupta, Sarah Sirajuddin, D. Sculley, Rajat Monga, Greg Corrado, Fernanda B. Viegas, Martin Wattenberg

* 10 pages 

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BriarPatches: Pixel-Space Interventions for Inducing Demographic Parity

Dec 17, 2018
Alexey A. Gritsenko, Alex D'Amour, James Atwood, Yoni Halpern, D. Sculley

* 6 pages, 5 figures, NeurIPS Workshop on Ethical, Social and Governance Issues in AI 

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Predicting Electron-Ionization Mass Spectrometry using Neural Networks

Nov 21, 2018
Jennifer N. Wei, David Belanger, Ryan P. Adams, D. Sculley

* 12 pages, 5 figures, accepted to Machine Learning for Molecules and Materials Workshop at NeurIPS 2018 

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No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World

Nov 22, 2017
Shreya Shankar, Yoni Halpern, Eric Breck, James Atwood, Jimbo Wilson, D. Sculley

* Presented at NIPS 2017 Workshop on Machine Learning for the Developing World 

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Direct-Manipulation Visualization of Deep Networks

Aug 12, 2017
Daniel Smilkov, Shan Carter, D. Sculley, Fernanda B. Viégas, Martin Wattenberg


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AutoMOS: Learning a non-intrusive assessor of naturalness-of-speech

Nov 28, 2016
Brian Patton, Yannis Agiomyrgiannakis, Michael Terry, Kevin Wilson, Rif A. Saurous, D. Sculley

* 4 pages, 2 figures, 2 tables, NIPS 2016 End-to-end Learning for Speech and Audio Processing Workshop 

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Large-Scale Learning with Less RAM via Randomization

Mar 19, 2013
Daniel Golovin, D. Sculley, H. Brendan McMahan, Michael Young

* Extended version of ICML 2013 paper 

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