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  1. proslijedio/la je Tweet
    11. svi 2019.

    One of my big picture takeaways from ICLR is that 2019 will be an exciting year for unsupervised learning!

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    8. srp 2018.

    Off to ICML'18 to present a tutorial on "Toward Theoretical Understanding of Deep Learning" Tuesday 1pm. Lecture slides and bibliography here.

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    5. srp 2018.

    Leon Bottou.... What doesn’t work is important to understand.

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    3. srp 2018.

    I will start a « oldies but goldies » series starting tomorrow (interleaved with more usual posts), featuring great papers that revolutionized computational mathematics and their applications. Here are some of the featured researchers.

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    3. srp 2018.

    The afternoon session of at kicks off with Jean Ponce’s lecture

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    27. lip 2018.

    Update on our (, and me) AI-ON project, on few-shot music generation: Thanks to our contributors, we now have 2 benchmarks and starter code for training. Want to collaborate on new models? Join our slack and see our github:

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    10. svi 2018.

    The wonderful art of and latent spaces on the main stage at

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  8. proslijedio/la je Tweet
    4. tra 2018.

    Just Starting : Interdisciplinary workshop: Levels, Hierarchies and Asymmetries Today : Marc Tittgemeyer, & David , Program on

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  9. proslijedio/la je Tweet
    20. pro 2017.

    Consider applying! I'll be participating, as well as many other great speakers. Note also that MLSS has some Fellowships available for students.

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    4. pro 2017.
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  11. proslijedio/la je Tweet

    A small reminder of the huge, ground-breaking discovery made by this year’s Physics Laureates! Learn more about the discovery:

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  12. proslijedio/la je Tweet
    3. pro 2017.

    FYI, the github repo for the project is here: . If you'd like to get involved, I'd suggest starting by reading the papers on our reading list.

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    We are relaunching the Artificial Intelligence Open Network (AI•ON), with 3 new open-source research projects from the groups of Yoshua Bengio, Hugo Larochelle and Max Welling. Get involved!

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    2. pro 2017.
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  15. proslijedio/la je Tweet
    2. pro 2017.

    The proximal operator is the implicit counterpart of the explicit gradient descent step. Fundamental to handle non-smooth optimization problems.

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  16. proslijedio/la je Tweet
    12. ruj 2014.

    Nesterov's accelerated method as a love child of gradient descent and mirror descent: (awesomely insightful paper)

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  17. proslijedio/la je Tweet
    6. stu 2017.

    New paper, VQ-VAE: learns phonemes & voice style transfer without supervision Audio samples:

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  18. proslijedio/la je Tweet
    23. stu 2017.

    An overview of gradient descent optimization algorithms

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  19. proslijedio/la je Tweet
    30. stu 2017.

    Facebook papers and activities at NIPS.

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  20. proslijedio/la je Tweet
    1. pro 2017.
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