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mccourt
searching PlanetScale…
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8 ms
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31.
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by
mccourt
10y ago
I've had this done to my feet before in Japan and China. One time it hurt and left a painful bruise for a couple days. Usually no problems or pain. Also no marks after the first couple times I had it done. Half the times I've
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by
mccourt
10y ago
Cool article. I wonder if the beach had any pertinent information/signage regarding the fruit. Obviously if the locals are aware then they wouldn't need it, but visitors would probably appreciate it. I wonder if it's more
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by
mccourt
11y ago
"... MathML is effectively preventing mathematics from aligning with today’s and tomorrow’s web." I'm probably one of the few that still likes to print things out or buy a physical copy of a book, but I also like reading/
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by
mccourt
11y ago
Hi everyone. This is the author and I'll be available for the rest of the day if anyone has any points of discussion. In particular, one goal I have for this post is to think about practical issues people have in approximation theory
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Some common problems in function approximation
(blog.sigopt.com)
2 points
by
mccourt
11y ago
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1 comments
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by
mccourt
11y ago
I'm happy to think on this with you, although it might take a little time to think about. One short answer I could point you to regarding this question is a topic called "local interpolation" using a compactly defined Lagrang
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by
mccourt
11y ago
Well, this is the difference in phrasing between the traditional statistical modeling setting and the terminology used in numerical analysis; perhaps this is why GPs are sometimes referred to as a nonparametric model. Also, I think you
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by
mccourt
11y ago
That may be. And I don't think kernels will ever be a hot topic. But part of that is that they are a very old topic (you can see Gauss referring to them in slide 22 of http://math.iit.edu/~fass/590/notes
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by
mccourt
11y ago
Okay. I'll see what I can do. No promises though - I may have taught probability recently, but I left all the hard problems to my students ;)
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by
mccourt
11y ago
I am not exactly sure what you are asking here, but I think that is more a terminology disconnect than anything. I haven't even heard someone say Vapnik-Chervonenkis dimension in a long time, so we may be coming at this from two diffe
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by
mccourt
11y ago
I need a bit of clarification here. In the list of length 100, each entry in that list is a binomial random variable X~Binom(10, .5). The variance of each of these binomials is Var(X) = 10(.5)(.5) = 2.5. But I don't think that's
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by
mccourt
11y ago
I tried to do some digging to find easy to access (both through the web, but also not terribly complicated) references on error bounds for kernels interpolation. I don't think there is one ... although the internet will surely correct
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by
mccourt
11y ago
Thanks for reading, I'm glad you enjoyed it. You are correct that there are few texts that discuss real-world examples of reproducing kernel Hilbert spaces without a significant amount of overhead to get there. In reality, I'm no
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by
mccourt
11y ago
I also get confused by the notation, so you are not alone. I think it is fair to say that kernel interpolation is a non-noisy kernel regression. Of course, this would also depend on your choice of terminology ... I use the word regression
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by
mccourt
11y ago
I am the author of these posts, and I am happy to answer questions if you have any.
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by
mccourt
11y ago
I am the author of these posts, and I am happy to answer questions if you have any.
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by
mccourt
11y ago
Hello, I am Mike, the author of this post, and I will be checking in for the rest of the day to answer questions.
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SigOpt Fundamentals: Approximation of Data
(blog.sigopt.com)
1 points
by
mccourt
11y ago
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1 comments
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Intuition behind Gaussian Processes
(blog.sigopt.com)
14 points
by
mccourt
11y ago
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1 comments
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by
mccourt
11y ago
This is Mike, I am the author of this post. Let me know if you have any questions; I will be checking in periodically throughout the day.
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Intuition behind Gaussian Processes
(blog.sigopt.com)
7 points
by
mccourt
11y ago
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1 comments