Jeremy.lee

@stl950116

Republic of Korea, interested in reinforcement learning, neuroscience Yonsei University,

Vrijeme pridruživanja: veljača 2013.

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  1. proslijedio/la je Tweet

    Wow, I also didn't know about this. I'll try it out next time I'm presenting! "It uses your computer’s microphone to detect your spoken presentation, then transcribes—in real time—what you say as captions on the slides you’re presenting. " (cont)

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  2. proslijedio/la je Tweet
    prije 22 sata

    We're celebrating the reviews that inspired us in 2019. Read the full collection, including the pick from : Reinforcement Learning, Fast and Slow

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    "One of the things I really like about this article is how it integrates work from the fields of artificial intelligence, psychology, neuroscience, and evolutionary theory." editor , picks Reinforcement Learning, Fast and Slow as her review of 2019

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  4. proslijedio/la je Tweet
    1. velj
    Odgovor korisnicima i sljedećem broju korisnika:

    Same! Would love to see your slides.

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  5. proslijedio/la je Tweet
    30. sij

    Amazing: every week I see a paper comparing algorithms using mean performance over *3* seeds ! Yes, ****3**** !!! Please please community, your great ideas will be served better using standard scientific methods!

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  6. proslijedio/la je Tweet
    30. sij

    We're standardizing OpenAI's deep learning framework on PyTorch to increase our research productivity at scale on GPUs (and have just released a PyTorch version of Spinning Up in Deep RL):

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  7. proslijedio/la je Tweet
    29. sij

    ‘Mapping the future’: our recent paper, which provides insight into previously unexplained elements of dopamine-based learning in the brain, is on the front cover of ! 🎉 Read the blog:

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  8. proslijedio/la je Tweet
    28. sij

    In “Artificial Intelligence, Values and Alignment” DeepMind’s explores approaches to aligning AI with a wide range of human values:

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  9. proslijedio/la je Tweet
    23. sij

    Google Dataset Search is now officially out of beta. "Dataset Search has indexed almost 25 million of these datasets, giving you a single place to search for datasets & find links to where the data is." Nice work, Natasha Noy and everyone else involved!

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  10. proslijedio/la je Tweet
    23. sij

    Q-learning is difficult to apply when the number of available actions is large. We show that a simple extension based on amortized stochastic search allows Q-learning to scale to high-dimensional discrete, continuous or hybrid action spaces:

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  11. proslijedio/la je Tweet
    20. sij

    Given the smoothness of videos, can we learn models more efficiently than with ? We present Sideways - a step towards a high-throughput, approximate backprop that considers the one-way direction of time and pipelines forward and backward passes.

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  12. proslijedio/la je Tweet
    15. sij

    We worked with to show that distributional RL, a recent development in AI research, can provide insight into previously unexplained elements of dopamine-based learning in the brain. Read the blog: (2/2)

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  13. proslijedio/la je Tweet
    6. pro 2019.

    Review paper on flows from the experts!

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  14. proslijedio/la je Tweet
    4. sij
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  15. proslijedio/la je Tweet
    6. sij

    How To Be Successful (At Your Career, Twitter Edition)

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  16. proslijedio/la je Tweet
    24. lis 2018.

    Excited to release our new multi-agent RL paper showing that when agents receive a social reward for having causal influence over other agents, it leads to enhanced cooperation and emergent communication

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  17. proslijedio/la je Tweet
    5. sij

    I couldn’t decide the topic of my next post. Would like to hear your ideas. Plz reply! Thanks <3

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  18. proslijedio/la je Tweet
    25. pro 2019.
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  19. proslijedio/la je Tweet
    21. pro 2019.
    Odgovor korisniku/ci

    may have some more thoughts, but I don't think we've worked through this yet! I got into this because of a genuine confusion at conferences where people would talk about "sampling from the posterior" in RL.. But their algorithm didn't seem like Thompson sampling!

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  20. proslijedio/la je Tweet
    20. pro 2019.

    Congratulations also to new member Kristian who is on two accepted papers with his old lab, including "Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery" - , Xinyang Geng, ,

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