Dorsa Sadigh

@DorsaSadigh

Assistant Professor in Robotics at Stanford University

San Francisco, CA
dorsa.fyi
Vrijeme pridruživanja: veljača 2014.
34 fotografije ili videozapisa Fotografije i videozapisi

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  1. 1. velj

    On challenges of learning human preferences...

    How do you teach an system to understand humans' preferences if humans aren't always sure what they want? HAI affiliates , Stuart Russell and Yoshua Bengio are exploring the answers.
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  2. 10. pro 2019.

    I will be missing . will present our work today on learning and influencing human decisions through routing and pricing autonomous vehicles. paper: The Green Choice: w/ , Daniel Lazar, Ramtin Pedarsani

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  3. 15. stu 2019.

    Stuart Russell speaking about a mathematical theory of care giving

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  4. 15. stu 2019.

    Excited to co-organize with Mark Mueller at UC Berkeley. Looking forward to a day full of awesome robotics talks:

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    13. stu 2019.

    My first attempt at a talk for a public audience, explaining some of the intricacies of human-robot coordination. Also a non-technical overview of work with , Jaime Fisac, , and collaborators from Claire Tomlin's group:

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  6. 11. stu 2019.

    And Krishnan Srinivasan!

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  7. 11. stu 2019.

    Our recent work on learning latent actions for making teleoperation easier and more intuitive: paper: w/ Dylan Losey, ,

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    11. stu 2019.

    ICYMI: Reminder that submissions for L4DC 2020 are now open. Deadline is December 6. We’re excited to read your contributions!

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  9. 3. stu 2019.

    I will be missing . Our papers: 1) Robots that Take Advantage of Human Trust. w/ Dylan Losey. paper: 2) Active Learning of Reward Dynamics from Hierarchical Queries. w/ , C. Basu, Z. He, M. Singhal. paper:

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    28. lis 2019.

    Four incredible women leaders on stage of today’s conf, sharing their thought leadership on ML fairness AI & economics tech & policy/regulation tech & national/international security & cooperations

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  11. 28. lis 2019.

    (2/2) And the second paper is: 2) Asking Easy Questions: A User-Friendly Approach to Active Reward Learning paper: w/ , Andy Palan, Nick Landolfi, and Dylan Losey.

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  12. 28. lis 2019.

    (1/2) I will be missing . We will have a spotlight on: 1) Learning from My Partner’s Actions: Roles in Decentralized Robot Teams paper: blogpost: w/ Dylan Losey, Mengxi Li, and .

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  13. 28. lis 2019.

    I am co-organizing the AI Safety Session tomorrow at 1-3pm. Trying to answer "What does safety mean and what should we do about it?" Speakers: , , James Zou, Tino Cuellar, Moses Charikar, Ritchie Lee, Maxime Bouton, and Erika Strandberg.

    Our fall conference on AI Ethics, Policy, and Governance kicks off today at 8:45 a.m. PT! Watch the livestream on our homepage:
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  14. 24. lis 2019.

    On our recent work on asking easy questions from humans to learn reward function w\ , Andy Palan, Nick Landolfi, and Dylan Losey. This will be presented next week at CoRL 2019. via

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    21. lis 2019.

    They have very different views on , but these experts were able to reach consensus on a promising policy roadmap: , Leslie Kaelbling, Stuart Russell, , , Bart Selman,

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    10. ruj 2019.

    Our recent work with Daniel A. Lazar, and Ramtin Pedarsani on learning dynamic routing of autonomous cars to decrease traffic congestion is on arxiv now:

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  17. 19. kol 2019.

    Our final talk of today, Maxime Bouton talking about point-based methods for model checking of POMDPs

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  18. 19. kol 2019.

    Aleksandar Zeljić discussing challenges that arise in verification of deep neural networks using Reluplex

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  19. 19. kol 2019.

    Alessio Lomuscio using parameterized model checking for fault tolerance of swarm robots

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  20. 19. kol 2019.

    Justice Tino Cuellar discussing how we should regulate AI systems: thinking about component level, system level, and societal level AI safety

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