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IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks

Jan 23, 2020
Michael Luo, Jiahao Yao, Richard Liaw, Eric Liang, Ion Stoica

* ICLR 2020 Publication; 14 pages, 10 figures 

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HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline

Jan 08, 2020
Richard Liaw, Romil Bhardwaj, Lisa Dunlap, Yitian Zou, Joseph Gonzalez, Ion Stoica, Alexey Tumanov

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Ray: A Distributed Framework for Emerging AI Applications

Sep 30, 2018
Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, Melih Elibol, Zongheng Yang, William Paul, Michael I. Jordan, Ion Stoica

* 17 pages, 14 figures, 13th USENIX Symposium on Operating Systems Design and Implementation, 2018 

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Tune: A Research Platform for Distributed Model Selection and Training

Jul 13, 2018
Richard Liaw, Eric Liang, Robert Nishihara, Philipp Moritz, Joseph E. Gonzalez, Ion Stoica

* 8 Pages, Presented at the 2018 ICML AutoML workshop 

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RLlib: Abstractions for Distributed Reinforcement Learning

Jun 29, 2018
Eric Liang, Richard Liaw, Philipp Moritz, Robert Nishihara, Roy Fox, Ken Goldberg, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica

* Published in the International Conference on Machine Learning (ICML 2018), 10 pages 

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Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning

Nov 04, 2017
Richard Liaw, Sanjay Krishnan, Animesh Garg, Daniel Crankshaw, Joseph E. Gonzalez, Ken Goldberg

* 8 pages, 11 figures 

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Real-Time Machine Learning: The Missing Pieces

May 19, 2017
Robert Nishihara, Philipp Moritz, Stephanie Wang, Alexey Tumanov, William Paul, Johann Schleier-Smith, Richard Liaw, Mehrdad Niknami, Michael I. Jordan, Ion Stoica

* 6 pages, 3 figures 

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HIRL: Hierarchical Inverse Reinforcement Learning for Long-Horizon Tasks with Delayed Rewards

Apr 21, 2016
Sanjay Krishnan, Animesh Garg, Richard Liaw, Lauren Miller, Florian T. Pokorny, Ken Goldberg

* 12 pages 

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