A map of racial segregation in the US.

Vi Hart explains serial music (h/t Jim CaJacob).

More adventures in trolling scam journals with bogus papers (h/t my father).

Brighten does some number crunching on his research notebook.

Jerry takes “disruptive innovation” to task.

Vladimir Horowitz plays a concert at the Carter White House. Also Jim Lehrer looks very young. The program (as cribbed from YouTube)

  • The Star-Spangled Banner
  • Chopin: Sonata in B-flat minor, opus 35, n°2
  • Chopin: Waltz in a minor, opus 34, n°2
  • Chopin: Waltz in C-sharp minor, opus 64, n° 2
  • Chopin: Polonaise in A-flat major, opus 53 ,Héroïque
  • Schumann: Träumerei, Kinderszene n°7
  • Rachmaninoff: Polka de W.R
  • Horowitz: Variations on a theme from Bizet’s Carmen

The Simons Institute is going strong at Berkeley now. Moritz Hardt has some opinions about what CS theory should say about “big data,” and how it might be require some adjustments to ways of thinking. Suresh responds in part by pointing out some of the successes of the past.

John Holbo is reading Appiah and makes me want to read Appiah. My book queue is already a bit long though…

An important thing to realize about performance art that makes a splash is that it can be often exploitative.

Mimosa shows us what she sees.

I was in New York on Sunday afternoon and on the suggestion of Steve Severinghaus we took a trip to the brand-new Museum of Mathematics, which is a short walk from the Flatiron building.

The Museum of Mathematics

The Museum of Mathematics


It’s a great little place to take kids — there are quite a few exhibits which illustrate all sorts of mathematics from recreational math and Martin Gardner-esque pastimes like tessellations to an interactive video-floor which draws minimum distance spanning trees between the people standing on it. It apparently does Voronoi tessellations too but it wasn’t in that mode when I was there. There’s also a video wall which makes your body into a tree fractal, games, and a car-racing game based on the brachistochrone problem. The kids were all over that so I just got to watch.

One of the nice things was that there was a touch-screen explanation of each exhibit from which you could get three different “levels” of explanation depending on how much detail you wanted, and also additional information and references in case you wanted to learn more. That’s good because I think it will let parents learn enough to help explain the exhibit to their kids at a level that the parents feel comfortable. That makes it a museum for everyone and not just a museum for math-y parents who want to indoctrinate their children. On the downside, a lot of the exhibits were broken or under repair or under construction, so we really only got to see about 2/3 of the things.

Apparently it’s also a good place to go on a first date, as evidenced by some surreptitious people-watching. So if you’re in New York and want a romantic or educational time (aren’t they the same thing?), go check it out!

Troubles in how science is marketed to girls.

Human remains at Richard III’s grave! (That sounds like a cryptic clue but it isn’t).

An interesting take on Karachi, but I’d want a local’s opinion of it…

The case of Aseem Trivedi is a real travesty.

Bad Lip Reading does a number on Mitt Romney. They’ve also done Obama.

Via Amber, a collection of grassroots feminist political posters from India.

Via John, some fun investigations on how 355/113 is an amazingly good approximation to \pi. Also related are the Stern-Brocot trees, which can give continued fraction expansions.

I had missed this speech by a 10 year old on gay marriage when it happened (I was in India), but it’s pretty heartwarming. For more background on how the principal originally deemed the story “inappropriate.”

What is a Bayesian?

Unrelatedly, ML Hipster — tight bounds and tight jeans.

The ITA Workshop is here! Blogging will happen, I hope, but probably not as extensively as before.

An important look at 6th Street in San Francisco (h/t Celeste).

You got that right, Arnold Schwartzenegger.

Werner Herzog is sometimes off-puttingly weird, but this critique (until around 3 min) is on-point (h/t B.K.).

The Death of the Cyberflâneur (h/t Mimosa). I am looking forward to being a flâneur in Chicago. The mild winter has helped, but I am rather looking forward to the spring for it. For now I suppose I am more of a cyberflâneur… Also, I hate the prefix “cyber.”

I saw Scott’s talk today on some complexity results related to his and Alex Arkhpov’s work on linear optics. I missed the main seminar but I saw the theory talk, which was on how hard it is to approximate the permanent of a matrix X whose entries (X_{ij}) are drawn iid complex circularly-symmetric Gaussian \mathcal{CN}(0,1). In the course of computing the expected value of the 4th moment of the permanent, he gave the following cute result as a puzzle. Given a permutation \sigma of length n, let c(\sigma) be the number of cycles in \sigma. Suppose \sigma is drawn uniformly from the set of all permutations. Show that

\mathbb{E}[ 2^{c(\sigma)}] = n + 1.

At least I think that’s the statement.

In other news…

  • Ken Ono has announced (with others) an algebraic formula for partition numbers. Very exciting!
  • Cosma thinks that New Yorker article is risible, but after talking to a number of people about it, I realized that the writing is pretty risible (and that I had, at first pass, skimmed to the part which I thought was good to report in the popular (or elitist) press, namely the bias towards positive results. Andrew Gelman points out that he has written about this before, but I think the venue was the more interesting part here. What was risible about the writing is that it starts out in this “ZOMG OUR SCIENCE POWERZ ARE FAAAAAAADINNNNNNGGGGGGG,” and then goes on to say slightly more reasonable things. It’s worthy of the worst of Malcolm Gladwell.
  • Tofu is complicated.
  • The 90-second Newbery contest.

I am a little surprised that this article by Amy Chua was even published, because it sounds completely crazy to me.

UPDATE : Still bad, but not as bad as it read?

Apparently I spend half my time reading Crooked Timber.

Žižek gets a lashing for his lazy contrarianism.

A great piece by Michael Bérubé on the Sokal hoax and its aftermath.

Scott Aaronson thinks people should vote to cut funding for quantum computing via YouCut. Why? Because “seeing my own favorite research topics attacked on the floor of the House” would be hilarious (and it would too!).

Marc Lelarge has a new paper up on diffusion and cascade effects in random networks. Fun reading for the break, assuming I can get time.

Some new ways of measuring impact factors.

This is a bit of a pessimistic list, but here are the top science/scientist retractions in 2010. This reminds me of a pretty interesting New Yorker article I just read on the difficulty in reproducing scientific results. The lingering feeling after reading that article is that we need better statistics than just blindly applying chi-square tests and blah blah blah.

I’ve seen this quote excerpted in parts before, but not the whole thing:

I repeat, feedback is a method for controlling a system by reinserting into it the results of its past performance. If these results are merely used as numerical data for the criticism of the system and its regulation, we have the simple feedback of the control engineers. If, however, the information which proceeds backward from the performance is able to change the general method and pattern of performance, we have a process which may well be called learning.
- Norbert Wiener, The Human Use of Human Beings

It is a strange distinction Wiener is trying to make here. First, Wiener tries to make “numerical data” a simple special case, and equates control as the manipulation of numerical data. However, he doesn’t contrast numbers with something else (presumably non-numerical) which can “change the general method and pattern.” Taking it from the other direction, he implies that mere control engineering cannot accomplish “learning.” That is, from numerical data and “criticism of the system” we cannot change how the system works. By Wiener’s lights, pretty much all of the work in mathematical control and machine learning would be classified as control.

I am, of course, missing the context in which Wiener was writing. But I’m not sure what I’m missing. For example, at the time a “control engineer” may have been more of a regulator, so in the first case Wiener may be referring to putting a human in the loop. In the book he makes a distinction between data and algorithms (the “taping”) which has been fuzzed up by computer science. If this distinction leads to drawing a line between control and learning, then is there a distinction between control and learning?

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