I have a subscription to Harper’s and try to solve the cryptic crossword each month in the vain hope that I will win a free year’s subscription. The puzzles back to 1976 have been posted online.
March 25, 2013
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January 3, 2013
Having seen a talk recently by John Ioannidis on how medical research is (often) bunk, this finer corrective by Larry Wasserman was nice to read.
Computer science conferences are often not organized by the ACM, but instead there are different foundations for machine learning and vision and so on that basically exist to organize the annual conference(s). At least, that is what I understand. There are a few which are run by the ACM, and there’s often debate about whether or not the ACM affiliation is worth it, given the overheads and so on. Boaz Barak had a post a little over a week ago making the case for sticking with the ACM. Given the hegemonic control of the IEEE on all things EE (more or less), this debate is new to me. As far as I can tell, ISIT exists to cover some of the cost of publishing the IT Transactions, and so it sort of has to be run by IEEE.
As mentioned before, Tara Javidi has a nice post up on what it means for one random variable to be stochastically less variable than another.
Paul Miniero has a bigger picture view of NIPS — I saw there were lots of papers on “deep learning” but it’s not really my area so I missed many of those posters.
David Eppstein’s top 10 cs.DS papers from 2012.
December 24, 2012
Via Allie Fletcher, here is an awesome video on the SVD from Los Alamos National Lab in 1976:
This film about the matrix singular value decomposition was made in 1976 at the Los Alamos National Laboratory. Today the SVD is widely used in scientific and engineering computation, but in 1976 the SVD was relatively unknown. A practical algorithm for its computation had been developed only a few years earlier and the LINPACK project was in the early stages of its implementation. The 3-D computer graphics involved hidden line computations. The computer output was 16mm celluloid film.
The graphics are awesome. Moler blogged about some of the history of the film. Those who are particularly “attentive” may note that the SVD movie seems familiar:
The first Star Trek movie came out in 1979. The producers had asked Los Alamos for computer graphics to run on the displays on the bridge of the Enterprise. They chose our SVD movie to run on the science officer’s display. So, if you look over Spock’s shoulder as the Enterprise enters the nebula in search of Viger, you can glimpse a matrix being diagonalized by Givens transformations and the QR iteration.
October 4, 2012
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Dhruv Batra forwarded this Communications of the ACM article by Pedro Domingos, entitled “A Few Useful Things to Know about Machine Learning” [free version] The main point from the abstract is:
However, developing successful machine learning applications requires a substantial amount of “black art” that is hard to find in textbooks. This article summarizes twelve key lessons that machine learning researchers and practitioners have learned. These include pitfalls to avoid, important issues to focus on, and answers to common questions.
The article focuses on the classification problem to illustrate these “key lessons.” It’s well-worth reading, especially for people who don’t work on machine learning because it explains a number of important issues.
- It illustrates the gap between what the theory/research works on and the nitty-gritty of applying these algorithms to real data.
- It gives people who want to implement an ML method important fundamental questions to ask before starting : how do I represent my data? How do I evaluate performance? How do I do things efficiently? These have to get squared away first.
- Domain knowledge and feature engineering are the keys to success.
Since I’m guessing there are 2 machine learners who read this blog, go read it (unless you are one of my friends who doesn’t care about all of these technical posts).
October 2, 2012
Via Erin (via Bruce Schneier’s blog), I found out about S. Parthasarathy‘s proposal to replace Alice and Bob with Sita and Rama. I have been known to use Alice and Bob on occasion (unlike some people I find the anthropomorphizing to be good, on the balance), but perhaps I should develop some cultural pride and make the switch to “a smarter alternative to these characters.” According to Parthasarathy, there is greater literary relevance to the scenario where Sita wants to send a message to Rama. The dramatic personae in this version are:
- Sita : kidnapped maiden who wishes to send a message
- Rama : brave prince who is to receive the message
- Hanuman : the honest broker who relays the message
- Ravana : the rogue-in-the-middle who acts as the adversary. To avoid confusing first letters, let’s rename him Badmash.
There are a number of other appealing allusions in this scenario.
I think it’s a fun exercise — can one come up with other settings? Perhaps based on Gilgamesh, or Star Wars. I’m sure at least one reader of this blog could come up with a Battlestar Galactica scenario. Adama to Baltar?
Also, I couldn’t help but point to this chestnut, the real story of Alice and Bob (h/t to my father).
October 1, 2012
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September 19, 2012
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DIMACS Workshop on Differential Privacy across Computer Science
October 24-26, 2012
(immediately after FOCS 2012)
Call for Abstracts — Short Presentations
The upcoming DIMACS workshop on differential privacy will feature invited talks by experts from a range of areas in computer science as well as short talks (5 to 10 minutes) by participants.
Participants interested in giving a short presentation should send an email to firstname.lastname@example.org containing a proposed talk title, abstract, and the speaker’s name and affiliation. We will try to
accommodate as many speakers as possible, but
a) requests received before October 1 will get full consideration
b) priority will be given to junior researchers, so students and postdocs should indicate their status in the email.
More information about the workshop:
The last few years have seen an explosion of results concerning differential privacy across many distinct but overlapping communities in computer science: Theoretical Computer Science, Databases, Programming Languages, Machine Learning, Data Mining, Security, and Cryptography. Each of these different areas has different priorities and techniques, and despite very similar interests, motivations, and choice of problems, it has become difficult to keep track of this large literature across so many different venues. The purpose of this workshop is to bring researchers in differential privacy across all of these communities together under one roof to discuss recent results and synchronize our understanding of the field. The first day of the workshop will include tutorials, representing a broad cross-section of research across fields. The remaining days will be devoted to talks on the exciting recent results in differential privacy across communities, discussion and formation of interesting open problems, and directions for potential inter-community collaborations.
July 6, 2012
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I’m being lazy about more ISIT blogging because my brain is full. So here are some links as a distraction.
Via John, George Boolos’s talk entitled Gödel’s Second Incompleteness Theorem Explained in Words of One Syllable.
D’Angelo is back!
This short video about a subway stair in New York is great, especially the music.
Luca’s thoughts on the Turing Centennial are touching.
April 17, 2012
Bret Victor talks about Inventing on Principle — the first half are a lot of demos of some pretty amazing applications of his major driving principle, which is that creators should be able to see what they are creating in real time. He sometimes waxes a little TED-like, but overall, quite inspiring.
March 29, 2012
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