Somewhat related field, compressive sensing, attempts to answer some of those questions (particularly missing data, uneven sampling and errors) using a L1 minimisation technique.
That was actually fantastic. The professor is quite goofy, but he really goes over everything from first principles and goes through a real example - constructing a solution without any cheating :))
I was a bit bummed out there weren't a lot of Compressed Sensing libraries around, but it seems you just need a "convex optimization" routine (aka linear programming). And these seem to exist in every language
I'll try to play around with this!
Thank you so much
From the video tutorial is seems relatively straightforward. I guess the basis selection is a fundamental issue that will be problem-specific.
I will have to try it with some concrete examples. The first question I have is, will it still work if you have a lot of high frequency noise? In the cases I'm thinking either there is measurement noise or just other jitter. So while the lower frequencies are sparse but I guess the higher frequencies not so much. I can't bandpass the data b/c it's got lots of holes or it's irregularly spaced.
>You imagine that XSLT is more secure but it’s not. It’s never been. Even pure XSLT is quite capable of Turing-complete tomfoolery, and from the beginning there were loopholes to introduce unsafe code.
It looks like it was fun, and I think that was the point.
I've done freeform electronics before, using wiring that was mainly the snipped-off legs of through hole resistors. I guess if you were fancy you could buy some bus wire. The assemblies are horrific to look at, and I love them.
Ok, so by that definition a geodesic sphere has the Rupert property, as the sphere is an approximation made up of equilateral triangles. What if we perform isotropic subdivision on the equilateral triangles, such that each inserted point lies on the sphere, centred on each base triangle. We then subdivide each base triangle by constructing 3 new triangles around the inserted point. Thus at each iteration, geodesic sphere of N triangles is subdivided into 3*N triangles. If we continue with the subdivision, each iteration is a refinement of the geodesic sphere, and the geometric approximation gets closer to the shape of a true sphere. As N approaches infinity, the Rupert property holds true (according to the definition). What happens at infinity?
At infinity, the shape becomes a sphere and all orientations of it are identical. It is no longer a convex polyhedron and, thus, not subject to consideration.
A sphere is not an infinity-sided polyhedron. It's a sphere. It's also the limit of a sequence of polyhedra, each of which does not have infinity sides. Just like aleph-null is the limit of the sequence of natural numbers, but is not a natural number.
Would it? I would've thought there is enough dust in the solar system that it would create constant xray emissions. Even if it's faint, it would stick out like a sore thumb on super sensitive xray telescopes.
An asteroid-mass black hole is around a micron across. It's not going to be nomming on much because the matter distribution inside the solar system isn't that dense.
Any tiny black hole born in the big bang would either have evaporated (if Hawking was right...) or would have grown much larger by now.
Even a moon-mass black hole (0.1mm) wouldn't be eating much, although its gravitational effects would be much more obvious.
>IMHO the actor model is great until you need to share something across processes
Incidentally that's what actors are designed for, passing data and being able to mutate their state without use of explicit synchronisation. You either copy or transfer ownership of data from one actor to the next via message passing. Actual sharing should be only done if the data in question is globally immutable.
> I don't expect politicians to be smart. I expect them to be good listeners and be the voice for the people.
I want both. I want them to be smart -- not necessarily domain expert smart, but reasonably smart with making life changing decisions for everyone. And base those decisions on recommendations made by domain experts.
I view touch screens, keyboards and mice as the saddle points in the usability landscape. These kinds of decides don't change much because their designs have converged to an efficient form factor, from a usability perspective. That does not mean there is nothing better, perhaps these devices sit in a false saddle point, and perhaps there is something better that has not been invented yet.
I wouldn't be surprised if this will be fixed sometime in the future.
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