Xiaohu ZHU

@neil_uai

A Watchful Guardian for AGI.

Shanghai, China
Vrijeme pridruživanja: veljača 2012.

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  1. Prikvačeni tweet
    14. lip 2019.

    Keep people aligned on AGI/AI all over the world.

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  2. proslijedio/la je Tweet
    1. velj

    On challenges of learning human preferences...

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  3. proslijedio/la je Tweet
    17. sij

    Cool theory paper presenting a problem that: - can be efficiently learned by SGD with a DenseNet with x^2 nonlin, - cannot be efficiently learned by any kernel method, including NTK.

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  4. proslijedio/la je Tweet
    16. sij

    How can we predict and control the collective behaviour of artificial agents? Classical game theory isn't much help when there are >2 agents. In our paper, we find markets impose useful structure on interactions between gradient-based learners:

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  5. proslijedio/la je Tweet
    15. sij

    Is deep learning is actually performing DEEP learning? We may have given the first proof that neural network is capable of efficient hierarchical learning, while existing theory only shows that deep learning can "simulate" non-hierarchical algorithms

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  6. proslijedio/la je Tweet
    4. sij

    Enough people asked about Coq vs Lean and setoids vs quotients that I tried to summarize what I know:

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  7. proslijedio/la je Tweet
    8. sij

    Studying or teaching Complex Analysis? This online book might be useful. ⭐️Complex Analysis: A Visual and Interactive Introduction⭐️ 🔗 Thanks everyone for your suggestions and reporting issues to improve this project.

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  8. proslijedio/la je Tweet
    9. sij

    I think it is clear that no AI we have at present can create life supporting systems on Mars, nor create new knowledge about cancer or black holes. Much work lies ahead and everyone seriously working on AI knows this fact. Let’s get down to work! Time is ticking.

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  9. proslijedio/la je Tweet
    8. sij

    Big shout out to the wildlife rescuers in Australia (pic: David Mariuz)

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  10. proslijedio/la je Tweet
    13. pro 2019.
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  11. proslijedio/la je Tweet
    15. pro 2019.

    Self-knowledge is the most valuable kind of knowledge, because all knowledge must be filtered through the self. If you don't understand the instrument, you don't understand the measurement.

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  12. proslijedio/la je Tweet
    8. pro 2019.

    Oldies but goldies: Frank Rosenblatt, The Perceptron-a perceiving and recognizing automaton, 1957. The first appearance of a neural network (single layer), later generalized to multiple layers.

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

    At OpenAI, we're excited by work in learned optimizers such as Learning To Learn By Gradient Descent By Gradient Descent. These methods will improve the efficiency of our models, and allow for higher quality science. Looking for a founding team member!

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  14. proslijedio/la je Tweet

    Many grand AI challenges remain. If you want to join our mission alongside me, , , & others, check out our scholarships & open roles. 3/3

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  15. proslijedio/la je Tweet
    3. pro 2019.

    This is a great extension of Coin Run, really curious to see what research it will inspire!

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  16. proslijedio/la je Tweet
    2. pro 2019.

    The max and soft-max (log-sum-exp) of convex functions is convex. Countless applications, from convex duality to exponential families.

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  17. proslijedio/la je Tweet
    1. pro 2019.

    This is a resurrection plant. It’s a desert plant that can survive almost complete desiccation. During the dry weather it curls into a tight ball, uncurling when exposed to moisture

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  18. proslijedio/la je Tweet
    3. pro 2019.

    Postdoc positions in theoretical machine learning at Princeton CS Dept. Relevant faculty include Elad Hazan, Ryan Adams, Yoram Singer, and me. Mention in cover letter which faculty you are interested in. Best to apply by Dec 15; latest by Jan 10.

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  19. proslijedio/la je Tweet
    1. pro 2019.

    Fantastic analogy from deconstructing the strange but popular school of thought that because deep learning isn't perfect the solution must be to combine it with symbolic AI.

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  20. proslijedio/la je Tweet
    30. stu 2019.

    A mean field evolution is the large number limit of particles systems. The simplest case is gradient descent, which corresponds to an advection equation in the limit.

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  21. proslijedio/la je Tweet
    28. stu 2019.

    Birkhoff’s contraction for Hilbert’s metric is a key tool to quantify convergence of Markov-Chains (Perron-Frobenius).

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