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iamaaditya

HN member
Joined
Thu, May 08, 2014, 3:47 AM UTC
HN karma
163
Public activity
25 items

About iamaaditya

https://iamaaditya.github.io Researcher in Computer Vision and Deep Learning hnchat:45cQ6ei61C6gkF6dW4R5 7d5e9cd6ac0f2955ccace9b89e5223a6bcb5945968778fa95615c6e9796f452e

Recent public activity

  1. comment
    Comment #46349502

    One usage case that I saw myself is when a vehicle is parked such that it will require the other vehicle to go slighty over the curb, in this case the curb is flat so I assuming th…

  2. comment
    Comment #31425887

    In machine learning (especially deep learning or neural networks), the 'training' is done by using Stochastic Gradient Descent. These gradients are computed using Backpropagation. …

  3. comment
    Comment #26267768

    Love the UI and the simple design. All the best with the product!

  4. comment
    Comment #25805886

    I believe there is some form of memory bias or bias in reporting by the media. If you look at the record books, you will find that most records are held by Sherpas. For example, mo…

  5. comment
    Comment #23766263

    Graham's Number, as in 3 ↑↑ 3, is named after Ron Graham. [1] https://plus.maths.org/content/too-big-write-not-too-big-gra... [2] https://en.wikipedia.org/wiki/Graham%27s_number?ol…

  6. story
  7. comment
    Comment #17675838

    [The Matrix Calculus You Need For Deep Learning]( https://arxiv.org/pdf/1802.01528.pdf )

  8. comment
    Comment #17280390

    One simple way to minimize impact of these attacks is our work called Pixel Deflection (CVPR 2018 Spotlight). Here is a short (4 min) video introduction to the idea https://youtu.b…

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  10. comment
    Comment #16281771

    Paper: https://arxiv.org/abs/1801.08926 Code: https://github.com/iamaaditya/pixel-deflection

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  13. comment
    Comment #13595989

    Technically it was heat but mostly it was due to (i) Economics, there was less demand for faster clock speed. Otherwise more research could have gone towards solving heat problem. …

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  15. comment
    Comment #13361725

    Recently, I have seen O1 being given pretty generously. Couple of people who I know who completed PhDs from mediocre University and less than 10 papers in total have all gotten the…

  16. comment
    Comment #13271260

    If it would be sufficient to have high PSNR only in the 'regions of interest', then you could use something like this [1], which uses a CNN model to predict a map, and a multiple J…

  17. comment
    Comment #13016590

    Here is my work, where I do use semantic information to achieve compression (rather improve JPEG). This is not an end to end compression like Google's work, but just incorporating …

  18. comment
    Comment #12433192

    This library does not bundle Intel MKL. It is a prerequisite.

  19. comment
    Comment #11718464

    https://support.microsoft.com/en-us/kb/3053711 (from the link) Resolution To resolve the issue, do not create a user account contains the string "user" on the computer.

  20. comment
    Comment #11668718

    This reminds me of ensemble. Most machine learning techniques benefit in accuracy and precision by ensembling different methods. More different the methods are (variance) better im…

  21. comment
    Comment #11436642

    hi syllogism Right now everyone doing this is highly focussed on the competition and trying to beat the numbers. For that purpose certainly they would want to stick to predicting T…

  22. comment
    Comment #11436587

    1. Model Q+I [1] Q+I+C [1] ATT 1000 ATT Full ACC. 0.2678 0.2939 0.4838 0.4651 Where ATT Full represents using all the words in the vocabulary, as you can see it performs worse than…

  23. comment
    Comment #11436561

    So, I experimented with Skip-thought vectors (as question), to embody the the semantic knowledge about the question but that performed poorly, I mean very poorly. Tbh, I was surpri…

  24. comment
    Comment #11434757

    Even though this is "Question Answering", it is trained as a classification model. Thus the model will try to come up with one of the top "1000" answers it has seen during the trai…

  25. comment
    Comment #11434613

    Hi Harperlee I ran the question you asked -- "Are they playing tennis?" and following is the result 99.93 % yes 00.05 % no 000.0 % right 000.0 % left 000.0 % black and white