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UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes


May 27, 2022
Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby

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* Alexander and Andr\'e share the first authorship, all authors made significant technical contributions to this work 

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RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning


Nov 04, 2021
Sabela Ramos, Sertan Girgin, Léonard Hussenot, Damien Vincent, Hanna Yakubovich, Daniel Toyama, Anita Gergely, Piotr Stanczyk, Raphael Marinier, Jeremiah Harmsen, Olivier Pietquin, Nikola Momchev

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* https://github.com/google-research/rlds 

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TensorFlow-Serving: Flexible, High-Performance ML Serving


Dec 27, 2017
Christopher Olston, Noah Fiedel, Kiril Gorovoy, Jeremiah Harmsen, Li Lao, Fangwei Li, Vinu Rajashekhar, Sukriti Ramesh, Jordan Soyke

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* Presented at NIPS 2017 Workshop on ML Systems (http://learningsys.org/nips17/acceptedpapers.html

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Wide & Deep Learning for Recommender Systems


Jun 24, 2016
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, Rohan Anil, Zakaria Haque, Lichan Hong, Vihan Jain, Xiaobing Liu, Hemal Shah

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