miloshh

Is there some serious reason you need to upgrade? If so, then I think you can just unzip a fresh install and copy over the plugins you want (as .jar files) into the new directory structure. Apparently there are more ways to do this, though I didn't try: http://www.venukb.com/2006/08/20/install-eclipse-plugins-the...

Those are pretty strange. I am using it on a Mac right now, with no serious problems.

I'm not sure about the bundle creator, I never used that, but not being able to create a new file seems like some random little issue that's most likely fixable.

> Then there is the beast called Eclipse. It certainly seems like it should be able to do everything in the world... Yet it is buggy, its plugin architecture is a conflicting mess, and its performance is so abysmal...

I have used Eclipse for many years with multiple languages, and none of this is quite true. There is a bit of a learning curve, where you have to learn not to do some things that break it. :) But that just takes a few hours, and a bit of patience - after that you have many months of happy coding, where it just works...

Indeed, Eclipse for Java is just unbeatable. I just recently started using it for C++ and it also works surprisingly well. I find myself much more productive than in a text editor, especially in a large code base I didn't know before.

That is a cool story...

Though, may I add that Python (or any other modern programming language) can manipulate its own code as data - only not as gracefully as Lisp. In other words, a Lisp program is its own AST - but in other languages the AST is only a "parse" away (and Python specifically makes computing it very easy).

Agreed; unfortunately, the people that will immediately imagine hordes of terrorists entering the country pretending to be entrepreneurs form a significant portion of the electorate.

These kids are first generation Americans - they went to school in the US.

I meant intensity resolution (or color depth, as you say). Dynamic range is something else - it is the interval [darkest, brightest], or their ratio if you prefer.

That would just increase the resolution. The real problem is that the device is way too dark to display the levels of radiance you see on a bright day. Tone-mapping has to be used to bring those levels down, and there is no "correct" way to do that - one has to play with settings.

A much simpler explanation would be - people that are wealthy enough to choose where they would like to live are predominantly not African-American.

Doctors are actually very careful not to be overzealous in diagnosis. To meet the criteria for a real diagnosis, the symptoms must be "excessive, long-term, and pervasive".

Similarly, not everyone with "blues" is clinically depressed, and not everyone with unexplained weight loss has cancer... the folk estimates of the prevalence of these conditions are way overblown.

Actually, it might be that doctors are quite accurate with diagnosing ADHD. The problem is that the sample of kids that they even get to examine is already biased - they may be the younger ones, in which parents or teachers just observed immaturity (which is probably uncorrelated to ADHD). Just a guess - maybe the paper addresses this issue.

Note that I defined n as the input size...

You just painstakingly carried out the absolute analysis, which I know works.

Let X be the value in the envelope you have, and Y in the other one (X and Y are both random variables with well-known distributions). Then E[Y/X] = 1.25. That's what I wanted you to explain. You just keep saying that E[X] = E[Y], which I know.

Note that this paradox would not arise if X and Y were independent, since then E[Y/X] = E[Y] / E[X] = 1.

I agree the blog is excellent, and provides a great answer to the original question of this thread. Check it out!

That's not a very good example - square matrix multiplication is O(n^1.5) (where n is the input size) and extremely fast in practice.

(Though, as you say, there could still be an O(n) algorithm - this is not known).

What I said is true even for linear programming (a P-complete problem) - it has polynomial and efficient algorithms - though the latter are actually not polynomial in the worst case. :)

Very good summary.

Though I was just reading the synopsis, and the statistical physics part seems to be proven: "The 1RSB ansatz of statistical mechanics says that the space of solutions of random k-SAT shatters into exponentially many clusters of solutions when the clause density is sufficiently high. This phase is called 1dRSB (1- Step Dynamic Replica Symmetry Breaking) and was conjectured by physicists as part of the 1RSB ansatz. It has since been rigorously proved for high values of k. It demonstrates the properties of high correlation between large sets of variables that we will need."

I did not dig into the references yet, though.

Yeah, the common complaint against "P=NP would break cryptography" is "but what if the polynomial algorithm for (say) SAT is n^10000?". That is not very likely, in my opinion. Even though "polynomial" is not equivalent to "efficient", in practice all problems that have a polynomial algorithm also have an efficient algorithm.

I do not necessarily agree. There is a large number of open problems in computer science (especially in theory of complexity), and a correct proof of P != NP is very likely to use techniques that will help in resolving the other open problems. The techniques are also likely to change what we're learning in CS courses.

Ad 1 - Not sure what you're trying to say, all I said is that you don't know the distribution of A - if you knew it, you could make an informed decision on whether to switch.

Ad 2 - If you carry out the analysis you're trying to teach me, you'll find that the expected relative gain from switching is 1.25. Now explain that. (You'll also find that the expected absolute gain is 0 - that's not a paradox.)

"Nothing interesting about that scenario." OK, but let's say you're not allowed to see the contents of the envelope you picked.

In this case, the argument that by switching you get 125% on average still holds!

I'd claim that this is even more interesting and paradoxical than the scenario you're talking about, where your explanation is correct (the distribution of the bigger value is crucial for your decision, and you know nothing about it).

OK, now I see there are two slightly different possible formalizations of the problem:

1. You are told that the two envelopes contain amounts A and 2A, but you aren't told what A is. After you pick one envelope, you are allowed to open it, and then you're given the choice to switch. Here the optimal move depends on the distribution of A, and if you don't know it, you can't do much other than pick randomly. After some googling, this is the more common formalization, and it is analyzed in several math papers and blogs.

2. (The version I was assuming.) You are told that the envelopes have, say, $100 and $200. You pick one and you aren't allowed to open it yet. Now you're given the option to switch one last time. There is no problem with undefined priors and weird conditional probabilities in this version. However, the freaking paradox still holds! The expected value you get by switching is $150, no question about that. But the expected relative gain you get by switching is 1.25, there's also no question about that! This is the real paradox to me. Taking an expectation of a relative quantity is intuitively wrong, but why exactly?

Which three worlds? After you have picked one envelope, there are two possible relative outcomes - 2 and 0.5. The average is 1.25 - there is nothing wrong with the math, the only problem is that taking an average of two relative quantities is intuitively not useful for decision making. Putting the intuition on a formal grounding is not something you succeeded with.

"use of an impossible probability distribution" - this sounds interesting. Which exact distribution do you mean? To me it seems (though I might be wrong) that the distributions are perfectly valid.

You have a pair of random variables (X, Y) that take values (100, 200) or (200, 100) with equal probability. Then E[X] = E[Y] = 150, there is no question about that. Also, E[X/Y] = 1.25, there is also no question. The only question is why E[X] is useful and E[X/Y] is not useful for our decision making - and I honestly don't know why.

Well, of course you're right, as is yanowitz. But there is something unsatisfying about this explanation. Intuitively it is obvious, but why is the relative reasoning incorrect?

There is no formal distinction between absolute and relative quantities, and no theorem that says that expected values can only be taken from absolute quantities. There are just random variables, and these have some distributions, and they can be independent or not. Nothing prevents you from taking an expectation of a random variable that is a ratio of two other random variables.

Another angle - I could say that our definition of expected value, based on weighted arithmetic average, is completely arbitrary, and instead define my own expected value G[X], based on the geometric average. Suddenly, the relative approach becomes correct: sqrt(2 * 0.5) = 1, so the expected relative improvement from switching is 1. What the hell is going on?

I was just typing my comment while you posted yours. I absolutely agree with this. Especially the "fluidity of the hacky code" - the environment that makes cool research happen is often the opposite of clean software engineering.

Source code publication along with the paper is a great idea in theory, but there are several problems with it in practice.

The reason CS researchers do not usually publish their code has nothing to do with dishonesty - nobody is trying to hide their code because it does not really work, or anything like that. It's not even that people are worried of scooping, though that sometimes happens.

The main problem is that any time spent on cleaning up the code, packaging examples, writing instructions, answering bug complaints, etc. is time not spent on things that matter in academia - doing research, presenting it, and teaching students.

It might help if some conferences required source code submissions - but people might just submit to different conferences instead. The only real solution would be if funding agencies like NSF required that any projects funded through them have to release source code. This makes sense from a taxpayer's point of view, and would make the extra work acceptable (since everyone would have to do it).

Yes, but I think the GPU designers did the right thing here by not injecting "magic" gamma-correction functionality into the texture sampler. There are many operations done on textures before they become pixel colors, plus they are often used to store non-image information (positions, normals, CT densities) where gamma correction would be incorrect.If you care about correct tone-mapping (most games probably don't), you can correct your textures beforehand.

I just checked the public transit, and it's about 1.5 hours (BART to Union City, then bus to Palo Alto). So that's also viable, I'd say.

The GPU cores share RAM, so there is no need to have local copies. Though if you run out of the 4GB available on Tesla/Quadro cards, it gets more complicated (but so would it on the CPU).