chillee

26 ms·

1. 301.▲
   by chillee 9y ago

   Ah yes, I forgot. Deepmind just secretly computed all 10^100 board states for alphago... Neural nets have been very successful for a lot of things while also being overhyped, but dismissing it all as marketing hype is throwing the baby out
2. 302.▲
   by chillee 9y ago

   Demis Hassabis (CEO of deepmind) is a notable exclusion from this list. He was ranked only behind Judith Polgar at age 13 with a 2300 rating.
3. 303.▲
   by chillee 9y ago

   Not surprised it's a "blockchain" developer advocating for how easy it is to dethrone Google.
4. 304.▲
   by chillee 9y ago

   Hmm, what do you mean by that? Not sure what I could add to the nips website from what they provide
5. 305.▲
   by chillee 9y ago

   Yep I'm aware haha. I made https://chillee.github.io/OpenReviewExplorer/ , so I'd love if all conferences used openreview.
6. 306.▲
   by chillee 9y ago

   What's your problem with these lists? I don't think making these lists is necessarily incompatible with the peer review process. Orals or spotlight presentations at conferences are effectively "best of" lists anyways.
7. 307.▲
   by chillee 9y ago

   Openreview is only for iclr, so you'll be missing a lot of papers. To the above poster, in ML journals aren't the main means of publication. You want to look at conferences like ICLR, NIPS, CVPR, etc.
8. 308.▲
   by chillee 9y ago

   Agh I typed up a response but it got deleted somehow. But basically, I view there as being 3 layers of understanding. For whatever level you're stuck at, there's different ways to get "unstuck". 1. Understand the task th
9. 309.▲
   by chillee 9y ago

   Yep, from the paper: > It is worth noting the parallels to Generative Adversarial Networks (GANs [7]), with the student playing the role of generator, and the teacher playing the role of discriminator. As opposed to GANs, however, the st
10. 310.▲
    by chillee 9y ago

    I'm a bit confused about the point that you're stating. I've never seen anybody not group GANs under machine learning. Machine learning is typically split into supervised learning, unsupervised learning, and reinforcement lea
11. 311.▲
    by chillee 9y ago

    Huh? GANs are for graphics, not machine learning? I mean, first of all, how are GANs not machine learning? They are definitely "machine learning", and I don't think anyone would disagree. Second of all, GANs are most definite
12. 312.▲
    by chillee 9y ago

    I don't think we're really disagreeing here. Afaik, hard bounds aren't a well defined mathematical concept, and it's fine to have different ones. What I initially meant by "hard bounds" was any kind of mathemat
13. 313.▲
    by chillee 9y ago

    "second to none"? In ML at least, I'd consider them second to many many companies.
14. 314.▲
    by chillee 9y ago

    The statement "deep neural networks are not affected by poor local minima" is not really a personal opinion/theory at this point; it's the dominating consensus in the research community. These are not just theoretical re
15. 315.▲
    by chillee 9y ago

    That's why I said high dimensional neural networks. There's been a lot of literature explaining why local minima aren't a problem in very high dimension loss surfaces. Check any of the literature on this subject: https:&#x2F
16. 316.▲
    by chillee 9y ago

    I'm not trying to pretend otherwise. Of the problems on this list, I think adversarial examples and bias are real problems. > Some of them are illuminating parts of ML that are problems (copying society's bias, adversarial atta
17. 317.▲
    by chillee 9y ago

    I think I'd still consider those bounds in the form x% chance that the result is within epsilon of optimum as hard. Otherwise, you'd have to discount the entire field of randomized algorithms as not having hard proofs.
18. 318.▲
    by chillee 9y ago

    Sorry, saw this late. It's a shown/kind of proven result that deep neural networks don't fall into local minima in the very high dimensional parameter space. GANs and reinforcement learning are different. Research on getting
19. 319.▲
    by chillee 9y ago

    Assuming you're talking about me, what in my comment came off as defensive? I definitely do not consider myself part of the whole "futurology"/Elon Musk/AGI in 15 years group, but I don't think this list exempl
20. 320.▲
    by chillee 9y ago

    Could you elaborate on what you consider these "problems" are? The way I would break down these "problems" are: Overhyped marketing (Face ID, Las Vegas self-driving bus, HSBC voice id, "AI imagines a Bank Butt sunse
21. 321.▲
    by chillee 9y ago

    While his reply seems like a hammer in search of a nail, his general point has merit, and is something that has been a topic of contention recently in deep learning (with Ali Rahimi's NIPS talk). What he calls formal verification is wh
22. 322.▲
    by chillee 9y ago

    Some of these are pretty eh. "Facebook chatbot shut down" doesn't really show anything. It was a everyday failure of training that got overblown in the media. "Google AI looks at rifles and sees helicopters": This w
23. 323.▲
    by chillee 9y ago

    We do have a long way to go, but AI has made huge strides over the past few years, irrespective of the hype/marketing. Notably this year, AlphaZero, advances in generating images ( https://github.com/tkarras/progres
24. 324.▲
    by chillee 9y ago

    But local minima aren't a problem for modern neural networks that are optimizing in very high dimensional space.
25. 325.▲
    by chillee 9y ago

    I think my math is pretty good... for an undergrad at least. Problem is that the barrier for contributing meaningful research in ML theory is higher than in applied ML haha. Anybody can read an applied paper like resnet and get the main ide
26. 326.▲
    by chillee 9y ago

    I agree that the sort of sampling bias/distributional shift you mention is definitely a real problem in deep learning. It so happens that yesterday I read a blog post that elaborates on this problem clearer than I can. Although it&#x27
27. 327.▲
    by chillee 9y ago

    I kind of agree. Whether or not you disagree with their strategy of blocking foreign tech companies, it's lead to an explosion of major chinese tech companies. Europe doesn't have a Google, Facebook, or Amazon, because the major U
28. 328.▲
    by chillee 9y ago

    Probably the single best article I saw recently was this: http://www.offconvex.org/2017/12/08/generalization1/ I think that blog post references most of the relevant papers as well, but if not, check the
29. 329.▲
    by chillee 9y ago

    Sorry, my last sentence > Otherwise, models can achieve very good generalization. was probably unclear. When we talk about generalization, we typically have to assume a lack of distributional shift. Otherwise, if the "truly unseen d
30. 330.▲
    by chillee 9y ago

    Basically, it's when your distribution that your classes come from change between training and test. For example, if after training your classifier to distinguish between cats and dogs, all of a sudden society decides that all white ha