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Chlorophyll: synthesis-aided compiler for low-power spatial architectures.
Phitchaya Mangpo Phothilimthana, Tikhon Jelvis, Rohin Shah, Nishant Totla, Sarah E. Chasins, Rastislav Bodík: Chlorophyll: synthesis-aided compiler for low-power spatial architectures. PLDI 2014: 396-407
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SIMPL: A DSL for Automatic Specialization of Inference Algorithms.
Rohin Shah, Emina Torlak, Rastislav Bodík: SIMPL: A DSL for Automatic Specialization of Inference Algorithms. CoRR abs/1604.04729 (2016)
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Active Inverse Reward Design.
Sören Mindermann, Rohin Shah, Adam Gleave, Dylan Hadfield-Menell: Active Inverse Reward Design. CoRR abs/1809.03060 (2018)
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On the Utility of Learning about Humans for Human-AI Coordination.
Micah Carroll, Rohin Shah, Mark K. Ho, Thomas L. Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan: On the Utility of Learning about Humans for Human-AI Coordination. CoRR abs/1910.05789 (2019)
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On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward...
Rohin Shah, Noah Gundotra, Pieter Abbeel, Anca D. Dragan: On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference. CoRR abs/1906.09624 (2019)
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Preferences Implicit in the State of the World.
Rohin Shah, Dmitrii Krasheninnikov, Jordan Alexander, Pieter Abbeel, Anca D. Dragan: Preferences Implicit in the State of the World. CoRR abs/1902.04198 (2019)
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On the Utility of Learning about Humans for Human-AI Coordination.
Micah Carroll, Rohin Shah, Mark K. Ho, Tom Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan: On the Utility of Learning about Humans for Human-AI Coordination. NeurIPS 2019: 5175-5186
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On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward...
Rohin Shah, Noah Gundotra, Pieter Abbeel, Anca D. Dragan: On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference. ICML 2019: 5670-5679
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Preferences Implicit in the State of the World.
Rohin Shah, Dmitrii Krasheninnikov, Jordan Alexander, Pieter Abbeel, Anca D. Dragan: Preferences Implicit in the State of the World. ICLR (Poster) 2019
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The MAGICAL Benchmark for Robust Imitation.
Sam Toyer, Rohin Shah, Andrew Critch, Stuart Russell: The MAGICAL Benchmark for Robust Imitation. CoRR abs/2011.00401 (2020)
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The MAGICAL Benchmark for Robust Imitation.
Sam Toyer, Rohin Shah, Andrew Critch, Stuart Russell: The MAGICAL Benchmark for Robust Imitation. NeurIPS 2020
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Choice Set Misspecification in Reward Inference.
Rachel Freedman, Rohin Shah, Anca D. Dragan: Choice Set Misspecification in Reward Inference. AISafety@IJCAI 2020
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Extracting and Using Preference Information from the State of the World.
Rohin Shah: Extracting and Using Preference Information from the State of the World. University of California, Berkeley, USA, 2020
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The MineRL BASALT Competition on Learning from Human Feedback.
Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca D....
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Learning What To Do by Simulating the Past.
David Lindner, Rohin Shah, Pieter Abbeel, Anca D. Dragan: Learning What To Do by Simulating the Past. CoRR abs/2104.03946 (2021)
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Combining Reward Information from Multiple Sources.
Dmitrii Krasheninnikov, Rohin Shah, Herke van Hoof: Combining Reward Information from Multiple Sources. CoRR abs/2103.12142 (2021)
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Choice Set Misspecification in Reward Inference.
Rachel Freedman, Rohin Shah, Anca D. Dragan: Choice Set Misspecification in Reward Inference. CoRR abs/2101.07691 (2021)
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Evaluating the Robustness of Collaborative Agents.
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah: Evaluating the Robustness of Collaborative Agents. CoRR abs/2101.05507 (2021)
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Optimal Policies Tend To Seek Power.
Alexander Matt Turner, Logan Smith, Rohin Shah, Andrew Critch, Prasad Tadepalli: Optimal Policies Tend To Seek Power. NeurIPS 2021: 23063-23074
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Retrospective on the 2021 MineRL BASALT Competition on Learning from Human...
Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries,...
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