Sunday, May 28, 2006

ESA PC Meeting: Day II

ETH Zurich was one of the first "foreign" universities I ever heard of. Pascal was the first "real" language I learnt, and I knew that the inventor of Pascal, Niklaus Wirth, was at ETH Zurich (he's retired now).

The ETH Computer Science building is very snazzy. From what I was told, it used to be inhabited by chemists, and there are still lab spaces with racks for beakers and spots for Bunsen burners (ooo, Bunsen burners, brings back memories of my dismal lab skills). There is at least one rather charming 'old-school' classroom that I saw, with wooden benches and fold-out desks. The look was somewhat marred by a very modern looking projector, and a computer screen on the front desk.

The department itself has a good geometry presence, with Emo Welzl , Bernd Gartner, and Michael Hoffman. It compares well (for CG) with places like Utrecht and the Free University of Berlin.

We managed to finish up earlier than scheduled today. The last few papers to be accepted always take the most time: it's like how the complexity of a system increases dramatically at a phase transition ! Overall, I think the main lesson I took back from looking at the papers is that experimental work takes a great deal of skill and effort. You have to tease out the interesting phenomena and design the right experiments to illustrate your points well. Word on the street is that far more good papers were submitted than there were slots available. It's an example of a trickle down effect that actually works !! As STOC, FOCS, and SODA have progressively become saturated, the quality of conferences like ESA is steadily increasing.

Sunday mostly everything is closed in Zurich. There is a nice hike one can do in the Uetliberg region (a hilly area that faces the lake). Was a good 1.5 hour hike, with distance markers not indicated by miles, but indicated in planetary fashion. The start point was the sun, the end point was pluto, and points in between represented the scaled distances of planets from the Sun. Geeky, but interesting.



It's time to go home...


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Saturday, May 27, 2006

ESA PC meeting, Day 1

This is a hectic time for me: I just got back from a workshop, and am now in Zurich for the ESA PC meeting, after which I go vortex hunting for a few days. Of course, my not-quite-10-month-old chose this exact weekend to get off his b*** and start slithering around on the floor.

Zurich is a nice town, and I emphasize the word 'town'. People remarked on how quiet the town appeared to be even on Friday and Saturday nights. We finally found the area where all the action was, but it was still quite small. The wonders of decentralization ! Apparently, Switzerland is so decentralized that you acquire citizenship by municipality or canton vote, rather than by any kind of nationalized process. My neighbours in Philadelphia barely know who I am :)

I had a good reason to like Switzerland even before I came here. It is the only place where an American green card is sufficient to enter the country: no annoying visa forms to fill out (Hindi-Swiss bhai bhai !!). My second reason to like Zurich in particular is that this is the first European city where I didn't feel like a homeless bum wearing the clothes that I did. Much of Western Europe is far too well-dressed for my slovenly tastes.

Where was I ? Oh yes, the PC meeting...

Of the major theory conferences that I am familiar with, STOC, FOCS, SoCG all have physical PC meetings, and ESA occasionally has one as well (they didn't have one last year). SODA most notably among the major conferences does NOT have a PC meeting: given the size of SODA PCs, this is not surprising.

Having a physical PC meeting creates an interesting dynamic. It has often been observed that people are much ruder on the internet than in real life; the relative anonymity of the Net appears to eliminate the social norms that pressure us into good behaviour. A physical PC meeting does tend to moderate sharp edges in our tendencies to do battle. As long as the PC chair can prune obvious rejects ahead of time in electronic discussions, like Thomas Erlebach did for us, we can have a fairly efficient meeting, and have reasonable discussions on all papers.

People put a lot of faith in scoring: it is interesting that high scores are not always a sure sign of acceptance. When people get together to discuss papers, far more nuances emerge, and overall I think this is a very good thing. Of course, all of this can happen in an electronic meeting as well; it's just that the process of deliberation feels very different. It's also quite a pleasure to meet face-to-face some of the people you might have had discussions with.

One day over; one more to go. Time to find some good Swiss chocolate (and no, I don't mean Lindt).


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Friday, May 26, 2006

Hales' detailed proof of Kepler's conjecture, in Disc. Comp. Geom.

Readers of this blog will be well aware of the interesting events surrounding Thomas Hale's proof of Kepler's conjecture:
...that close packing (either cubic or hexagonal close packing, both of which have maximum densities of pi/(3sqrt(2)) approx 74.048%) is the densest possible sphere packing
In short, his proof involved large amounts of computer verification, and after three years of intensive effort, the Annals of Mathematics determined that it could not verify with certainty that the proof was correct (not because there were problems, but because the proof had many "low-level components" that lacked a more general intuition, and were thus hard to verify, especially given the degree of computer search involved).

A strange arrangement was then made: the Annals of Mathematics published a briefer version of the proof, and made the code/data for the proof available unreviewed on its website. Discrete and Computational Geometry then undertook to publish detailed versions of the six preprints that Hales and his student S. P. Ferguson wrote in 1998.

That issue is now out, with a foreword by Gabor Fejes-Toth (who ran the committee that first attempted to verify the conjecture for Ann. Math) and Jeff Lagarias (much-missed AT&T alum who spent a significant amount of time and effort restructuring and clarifying the proofs from the original preprints.

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Wednesday, May 17, 2006

On the algorithmization of science

The latest issue of ACM's tree-killer has a Viewpoint by Thomas Easton on how algorithmic thinking pervades all areas of science (and soft science), and all I can say is, 'Hallelujah !':

Mathematics and algorithms are so essential to computational thinking that computer science will retain its historical emphases on these topics. Other fields that, like biology, have sought to mathematize their content will find that, because mathematics has incorporated algorithmic thinking, they might get closer to the queen by emphasizing algorithms over equations. Resistance is likely to be strong in the humanities, but even there algorithmic thinking is becoming essential. For example, it has found a niche through the way computers are used to verify that classic texts and artwork are properly attributed to their creators, to detect plagiarism, and even to aid the creative process.

More and more educators will have to grapple with the need for courses that inculcate algorithmic, or process-oriented, thinking. This might mean students will take more computer science courses. If this happens, computer science educators may need to redesign those courses to emphasize algorithmic thinking in ways that satisfy the needs of students in other fields, including those with only a distant relationship with mathematics.



(via Daniel Lemire)

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The more things change...

It's a common story (and one experienced by many):

Young student starts taking an interest in research
He studies hard, clears his apprenticeship, and starts publishing.
He has some success, and gains some recognition.
Starts to gain confidence, and branch out in his own sub area
Committees start rejecting his papers; frustration ensues
He tries other publications, and more rejections follow.
But his work is being recognized by those who appreciate him: funding follows slowly.
He creates a new conference, for misunderstood creators like himself.
It works for a while, but he gets disenchanted, and tries to go back to the more prestigious conferences.
More rejections, funding remains limited, but his fame grows and grows
Finally, he's so well known that his area gets its own name, and retrospectives are organized in his honor.

And who's the unfortunate researcher who exemplifies this trajectory ? It's Claude Monet !


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Thursday, May 11, 2006

Behavioral computing and airline loading...

Can distributed and local computing really be more efficient than centralized planning ? In economics of course, we know the answer, but in computing ?

Consider the problem: how to sequence passenger loading on an airplane so as to minimize completion time. In a Wired article by Dave Demerjian (pointer via Virginia Postrel), researchers proposed a "reverse pyramid" method (rear windows and middles before front aisles, roughly speaking) for loading passengers. The article also mentions "WILMA", or "Window-Middle-Aisle" order, and rotating zones (last 5 rows, first 5 rows, and so on), all of which are in use on different airlines.

Southwest however uses a different method, one that many of you are probably familiar with. Passengers are partitioned into three zones. Passengers enter by zone, and they sit wherever they want. According to the article,
...while Southwest's open seating might seem like an invitation for chaos, it actually illustrates a tendency among passengers to self-organize when left to their own devices. "Passengers who are free to sit anywhere usually do a good job staying out of each other's way," he explains. "Without having studied it in detail, I would imagine that an open boarding model is faster than assigned seating."
What we have here, ladies and gentleman, is an example of "Behavioral Computing". Michael Kearns at UPenn is one of the people investigating this space, and as he puts it,
Perhaps the computer science view of this fascinating line of thought can be best summarized as follows: Using relatively local information, distributed human organizations can compute good approximations to the all-pairs shortest paths problem. What other sorts of distributed optimization problems can humans networks solve?
Now this is not computing in the algorithmic sense: no n^2 time algorithms or NP-hardness results. But it reflects a growing interest in the "wisdom of crowds", social networks, and emergence phenomena (heck, even Charlie Eppes is working on 'cognitive emergence'). Kearns, and his students Nick Montfort and Siddharth Suri have some initial behavioral studies on graph coloring problems: there isn't a paper yet as far as I can tell, but I've heard about the results informally.

For those who might be wondering, this is not warmed-over distributed computing. Distributed computing indeed involved local computations, but the entities were slaves, devices that ran specific protocols that led to the desired outcome (leader election is a classic problem of this kind). There is a notion of malicious machines (a device that may have been compromised), and Byzantine agreement is a famous example of the kinds of problems one considers.

But the fundamental difference is that in this notion of behavioral computing, the local agents are not running pre-specified programs. They are often acting in their own interest, or working under some incentive model, ("I want to find the best seat quickly"), and may execute different procedures towards this goal. The key idea is to set up "a system that controls network structure, information conditions, incentives, and a variety of other variables of interest".

Thus, behavioral computing is more like distributed game theory, and fits nicely into the rapidly growing area of computational game theory.

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On rejection and reviews..

Lance, Luca and Oded have all weighed in on the matter of rejection letters and the proper frame of mind one views them with. Oded makes the important point about such things being about the allocation of scarce resources, rather than the assigning of value to a paper (or a candidate).

This alternate "frame" is crucial to understanding some of the more bizarre quirks in our conference review process. Theory conferences are (in)famous for short to non-existent comments to authors; it is not uncommon in certain other areas to gget pages and pages of comments back. However, you quickly learns that pages and pages of comments are usually as useless as a blank page in trying to determine why your opus didn't make it, while other piecees of %##$^&$ did.

Even the usual process of assigning scores is not useful, since the score indicates some absolute figure of merit, whereas many papers live or die based solely on the particular mix of submissions. In some conferences, it's even worse: you are required to give a paper a rating of the form "strong/weak accept/reject or neutral", essentially passing judgement on a paper in vacuo, as it were.

Once we accept (or realize) that conferences (especially nowadays) are about the allocation of scarce resources (speaking slots, or even 10 pages in the proceedings if you still insist on paper proceedings), then it becomes clear that trying to assign absolute scores and verdicts to papers without being able to compare with others is meaningless.

As a corollary, it means that any review process where reviewers don't get to see a large fraction of the papers is flawed. It also means that fetishizing the "feedback to authors" is also misleading. As Oded points out, this only gives an illusion of a value judgement where none can really be had.

It also has more radical implications for the way we design conference committees, (number of people, whether PC-submission is allowed, who gets to review what). But that's a tale for another post...
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Wednesday, May 10, 2006

Numb3rs reference: Neil Sloane's Online Encyclopedia of Integer Sequences

This week's episode of Numb3rs had a reference to Neil Sloane's (AT&T colleague) Online Encyclopedia of Integer Sequences. Charlie was attempting to backtrace where a network hacker was coming from, and discovered that his own code had been compromised. A secret code had been inserted, that spelt out a number sequence. Charlie was explaining this in class,
Student in Charlie's class: 23, 5, 18 is W E R in Sloane's Encyclopedia of
Integer Sequences. Maybe it's simple alphabet cipher?
(Thanks to Graham for the dialogue)

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Friday, May 05, 2006

Cryptorap...

Ever since Aaron Archer (aka A. Dogg) joined AT&T Labs, I've had half an ear out for funky CS raps. Enter MC Plus+:
MC Plus+ is the founder and indisputably the #1 greatest computer science gangsta rapper ever. He is to CS gangsta rap what a blue screen is to Windows, what Vaseline, maple syrup and sour cream are to a good time. He's putting CS on the map, producing raps for students from computer science departments around the world. With another 4 years still at Purdue, trying to get that PhD, he has promised to keep producing CS hip-hop for all the grad students in the struggle.
MC PLus+'s latest offering: Alice and Bob, a paean to cryptography...

(HT: BB)


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Sunday, April 30, 2006

"Geometry is not patented"

From Game 4 of the first-round playoff series between Miami and Chicago, Bill Walton and Steve Jones are arguing about whether a particular Heat offensive set was a triangle or not, and Walton says:
Geometry is not patented, Steve.
Indeed.
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Inadvertent Hashing and CDDB

Most people use the CDDB either knowingly or unknowingly. It's the backend to most computer CD players that downloads track/title information from a central site when you're playing a CD. Most player software allows you to add in information if CDDB doesn't return a hit, and I've done this every now and then. But overall I have been amazed by the hit rate of CDDB.

I assumed that CDs contained all the track information, and many do. But apparently, CDDB exploits an inadvertent hashing mechanism: the sequence of track times.
The CDDB database has information that allows your computer to identify a particular music CD in the CD drive and list its album title and track titles. Their service is used by RealJukebox, MusicMatch, WinAmp, and others. The title information is not stored on most CDs. The only information in the CD data is the number of tracks (songs) and the length of each. This is the information your CD player displays. What CDDB does is let the software on your PC take that track information, send a CD signature to CDDB through Internet protocols (if you're connected) and get back the titles. It works because songs are of relatively random length. The chances are good almost all albums are unique. (Figure there are about 10 songs on an album, and they each run from a minute and a half or so to three and a half minutes long, so the times vary by 100 seconds. There are 100x100x...x100 = 100**10 = 10**11 = 1 hundred billion = an awful lot of possible combinations.) An album is identified by a signature that is a special arithmetic combination of the times of all the tracks.

You'd figure that CDDB just bought a standard database with all the times and titles. Well, there wasn't one. What they did was accept Internet-relayed postings with the track timing information and the titles typed in by a volunteer.


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Wednesday, April 19, 2006

computers on stamps

Ultra neat (via BB). The irony of computers on stamps, considering what computers, (and email) have done to the postage business...



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Tuesday, April 18, 2006

on vision...

if you haven't already, do read Luca Trevisan's essay on perspective and taste in theoryCS.

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Monday, April 17, 2006

Bias in paper reviewing

Nowadays, I spend my time looking the most emailed articles on the NYT (or more uncharitably, "rating the competition"). An interesting Op-Ed from Sunday talks about bias in decision-making, and some of what the author says provides an interesting perspective on how we review papers.

Unlike in many other areas of computer science, theory papers are not reviewed double-blind; reviewers in general know the identity of the authors of a paper. I will say upfront that I don't think there is a real problem with this approach. It's not that I think that we are saintlier than reviewers in other disciplines; it's just that a combination of the nature of the subject and the value system of the area makes objective evaluations a little easier. However,
A Princeton University research team asked people to estimate how susceptible they and "the average person" were to a long list of judgmental biases; the majority of people claimed to be less biased than the majority of people. A 2001 study of medical residents found that 84 percent thought that their colleagues were influenced by gifts from pharmaceutical companies, but only 16 percent thought that they were similarly influenced.
We'd like to think that we can "factor out" the influence of author names when reviewing, but
Dozens of studies have shown that when people try to overcome their judgmental biases — for example, when they are given information and told not to let it influence their judgment — they simply can't comply, even when money is at stake.
What's also interesting is how we make decisions with limited information,
...researchers asked subjects to evaluate a student's intelligence by examining information about him one piece at a time. The information was quite damning, and subjects were told they could stop examining it as soon as they'd reached a firm conclusion. Results showed that when subjects liked the student they were evaluating, they turned over one card after another, searching for the one piece of information that might allow them to say something nice about him. But when they disliked the student, they turned over a few cards, shrugged and called it a day.
Or if you dislike a paper, you look for evidence to reject it, and if you like it, you look for evidence to champion it (rather than looking for evidence first, and making a judgement later).

And yet, all the people who scream 'Bias' when papers submitted to single-blind reviewing are rejected don't necessarily have a point:
And yet, if decision-makers are more biased than they realize, they are less biased than the rest of us suspect. Research shows that while people underestimate the influence of self-interest on their own judgments and decisions, they overestimate its influence on others.
What does all of this mean ? I am more biased than I think, but less biased than you think. It's good to keep that in mind (at least the first part), when reviewing papers. It's basic psychology after all.

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Saturday, April 15, 2006

Author Ordering, II

In the comments to my previous post, Janos Simon points out a pair of hilarious articles by Martin Tompa that were published in SIGACT News in 1990. The title of the first one is 'Figures of Merit', and in it, Tompa proceeds to define measures like the spotlight factor (basically the likelihood that you'd be first author if your co-authors were chosen randomly), and the coefficient of obliviousness (roughly speaking, how indifferent to fame you are by choosing co-authors prior in the order to you).

In his second article, Tompa updates the calculations after a year. As he puts it:
The purpose of this survey is to bring the community up to date on the most recent bounds, so that we may collaborate to improve them
I don't do the original articles justice with my dry rendition of their contents. You have to read them to encounter gems like:
There is one known instance in which a resourceful Ph .D . student named Yehuda
outspotlighted his advisor Shimon Even . When it came time to publish the results of
their collaboration, Even announced his inevitable intention of being first author. Yehuda responded by legally changing his name to Bar-Yehuda.
and, in his acknowledgements:
I thank the numerous contributors who inundated me with suggested additions after the Follies presentation, I can only wish that my serious research would stimulate half as much enthusiasm in the community.
The best line was a 'disacknowledgement' in part II (you'll have to read the articles for it to make complete sense):
Avi Wigderson refused to collaborate with anyone later in the alphabet, even in the interest of scientific advancement.
Update (4/16): Avi Wigderson reconsiders after 15three years of (unknowing) resistance !!
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Thursday, April 13, 2006

Author ordering on papers.

We order authors alphabetically in theory papers. The reasons for this are numerous, and not relevant; what's relevant is that this is often different from other CS communities, where the first-author, , last-author norm is usually followed (first-author being the person who did all the work, and last-author being the PI on the project).

I'm all for alphabetical ordering: it's easy and avoids annoying and often impossible-to-resolve discussions about who did "more" work on a paper. Note that it's easy to identify who did what; what's harder is comparing the relative merit of contributions, especially in the multi-authored extravaganzas that are common in theory.

It turns out though that alphabetical ordering may have one pitfall, at least in economics:
...a new paper (free, working version, Winter 06, JEP) demonstrates that these effects have important consequences for careers in economics. Faculty members in top departments with surnames beginning with letters earlier in the alphabet are substantially more likely to be tenured, be fellows of the Econometrics Society, and even win Nobel prizes (let's see, Arrow, Buchanan Coase...hmmm). No such effects are found in psychology where the alphabetical norm is not followed.
Well, I don't know about tenure, but I do know about ACM Fellows and Turing Award winners. I'm too lazy to do the linear regression that the authors do for their plots, but I will throw out these two tidbits: 60% of Turing award winners (30/50) have their last names in the first half of the alphabet [A-M], compared to 40% (20/50) in the latter half [N-Z]. With Fellows, the split is 63% (347/554) to 37% (207/554).

I don't know how the authors of this paper normalized against any skew in the base population of economists, and the numbers I quote are subject to the same objection. But just in case, call me Suresh Enkatasubramanian from now on.


Update (4/14): An anonymous poster and D. Sivakumar have been working hard to debunk my claim, successfully so far ! Anonymous points out that the percentage of names in [A-M] in their phone book is around 63%, and Siva reports that going by the DBLP database, around 62% of all authors are in the [A-M] range as well (the 50% cutoff is at K apparently). Now, although this "explains" my quick back of the hand statistics, it leaves two possibilities:
  • If one did the linear regression that the authors of the original paper used, one would get the same results
  • Even the authors of the original paper didn't correct for the baseline (and frankly, after reading their paper twice, I don't see where they did, but I can't imagine that they didn't).
A third point worth making is that CS has mixed policies on author ordering. Only theory consistenly uses alphabetical ordering, so it can be argued that the data cannot be used to infer anything at all.

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Monday, April 10, 2006

It's Vortex time...

Get your auras here ! And don't say you weren't warned. From the NYT:
A few years ago, USA Today called Sedona the most beautiful place in America. At sundown, that doesn't begin to cover it. And it's not just the views. There's a vibe in the air, something not quite audible, a kind of metaphysical dog whistle that calls people out to have a look around and to try to feel something that, if you're not a committed New-Age pilgrim, is hard to put into words. Nowhere else in this country does a natural setting feel so much like the inside of a soaring pantheistic cathedral.

Sunday, April 09, 2006

The Fib

Gregory K proposes a new form of mathematics-based poetry: the "Fib". The idea is simple: each line of the poem must have a number of syllables that equals the number at this position of the Fibonacci sequence. Example:
One
Small,
Precise,
Poetic,
Spiraling mixture:
Math plus poetry yields the Fib.
As Clive Thompson points out,
Even more lovely is the fact that the Fibonacci sequence officially begins with a zero. That means that the true first line of every Fib is always the same: Silence.
Start with a moment of rest. How beautiful.

Here's my 'umble contribution:

I
like
to blog.
Frequently.
Theory matters.
Computer science (theory)
is my home and geometric algorithms are
sublime. Let P be a set of points in general position in the plane. Amen.
Update (4/14): I was mentioned in the New York Times Book Section !
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Friday, April 07, 2006

CS blogs

Actually, there are far more CS blogs than the list David points to: here's an OPML file that you can import into a blog reader. It has 40+ blogs that are in some way connected to computer science.
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Thursday, April 06, 2006

SODA 2007

The CFP for SODA 2007 is out (thanks, Jeff). The humungous size of the geometry contingent is balanced by the humungous size of the commitee. This commitee has 27 folks, an increase of 4 over SODA 2006 and 2005. Submission counts have been going up by a little under 10% each year, and I guess Hal Gabow is also trying to reduce the load on each committee member: 500 * 3/27 = 55.56. Good luck, folks !!

In other news, short papers are still dead. May they rest in peace
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Wednesday, April 05, 2006

Mathematical Poetry

David Corfield writes a wonderful blog called "Philosophy of Real Mathematics", where he addresses
"what leading mathematicians of their day have achieved, how their styles of reasoning evolve, how they justify the course along which they steer their programmes, what constitute obstacles to these programmes, how they come to view a domain as worthy of study and how their ideas shape and are shaped by the concerns of physicists and other scientists".
His latest entry points us to another beautiful piece of mathematical poetry, this one written by no less than James Clerk Maxwell. The background for this poem is described in Corfield's post: I merely reproduce here the first stanza of the poem:

My soul's an amphicheiral knot
Upon a liquid vortex wrought
By Intellect in the Unseen residing,
While thou dost like a convict sit
With marlinspike untwisting it
Only to find my knottiness abiding,
Since all the tools for my untying
In four-dimensioned space are lying,
Where playful fancy intersperses
Whole avenues of universes,
Where Klein and Clifford fill the void
With one unbounded, finite homoloid,
Whereby the infinite is hopelessly destroyed.


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Saturday, April 01, 2006

60th birthdays

[Lowerbounds,Upperbounds] advertises MillerFest, a celebration of Gary Miller's 60th birthday. On April 24-25, Rutgers and DIMACS are hosting a workshop in honor of Joel Spencer's 60th birthday. Frieze Fest, last October, commemorated Alan Frieze's 60th birthday. I also hear that Peter Winkler's 60th will be commemorated next year, again at DIMACS.

What started the tradition of 60th birthday celebrations for researchers ? If you google '60th birthday mathematician', you get a very large number of links, as you do if you replace mathematician by physicist or economist. I looked all over attempting to find a source for this tradition, but it appears to go quite far back. I was wondering if any of my readers had any ideas about this...
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Friday, March 31, 2006

SWAT 06

The SWAT 06 results are out. More thoughts later.
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Thursday, March 30, 2006

Holy Joe Namath !!

AT&T Labs is located in Florham Park, in the middle of a large expanse of land formerly owned by Exxon and known as the Exxon complex.

Those who know me know that I am a rabid NFL fan.

Put these two facts together, and stir with a dose of this:

NY Jets moving HQ to Florham Park

Franchise will move its headquarters and training facility to the former Exxon complex

BY ROB JENNINGS
DAILY RECORD

FLORHAM PARK --The New York Jets will be building their new headquarters and training facility in Florham Park, Mayor Frank D. Tinari said today.

Under the agreement, the New Jersey Sports Exposition Authority will lease to the Jets 20 acres at the old Exxon site that it will be acquiring for $20 million, Tinari said.

The plan still awaits council and planning board approval, but Tinari was optimistic that the franchise defined by "Broadway" Joe Namath, Wesley Walker and Chad Pennington would soon be making its home in the borough.


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2006 Gödel Prize

Via my undergraduate advisor Somenath Biswas, and the IITK grapevine, comes the news that AKS (Manindra Agrawal, Neeraj Kayal and Nitin Saxena) will receive the 2006 Gödel Prize for their proof that PRIMES is in P.

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Wednesday, March 29, 2006

Grand Challenges ?

I've been thinking a lot about the Richard Hamming essay that [Lowerbounds,Upperbounds] mentioned a while ago. One of the things that he mentions is the need to work on "important problems":

If you do not work on an important problem, it’s unlikely you’ll do important work. It’s perfectly obvious. Great scientists have thought through, in a careful way, a number of important problems in their field, and they keep an eye on wondering how to attack them. Let me warn you, ‘important problem’ must be phrased carefully. The three outstanding problems in physics, in a certain sense, were never worked on while I was at Bell Labs. By important I mean guaranteed a Nobel Prize and any sum of money you want to mention. We didn’t work on (1) time travel, (2) teleportation, and (3) antigravity. They are not important problems because we do not have an attack. It’s not the consequence that makes a problem important, it is that you have a reasonable attack. That is what makes a problem important. When I say that most scientists don’t work on important problems, I mean it in that sense. The average scientist, so far as I can make out, spends almost all his time working on problems which he believes will not be important and he also doesn’t believe that they will lead to important problems.

I've been thinking about this section mainly because I started asking myself, "What are the important questions in computational geometry". Given all the TheoryMatters discussions of late, this question mutated itself into the (not-unrelated) question, "What are some of the grand challenges in computational geometry" ?

It's tricky to answer this question properly. It is quite easy to dash off a number of open problems in CG, but that is not so much the point of the second question. It's more about where the field is headed, and where we see some of the most interesting new problem areas opening up from.

Five or so years ago, the answer to this question might have been 'High Dimensional Approximate Geometry'. The core-set revolution has created a new set of techniques for dealing with approximate high-dimensional geometry, and this has fed off the developments in the theory of metric embeddings. I don't doubt that there is more work to be done here, but if we have to answer this question from the "funding perspective", i.e in terms of where geometry will be used next, I keep coming back to the issue of shape.

Some of the most important questions in biology over the next many years will involve structural analysis of proteins, and shape modelling is a key aspect of this. The work by Edelsbrunner and Mücke on alpha shapes connected ideas of shape to deeper ideas in combinatorial topology (the mathematical theory of shape, in one view), and the growing field of "computational topology" has been very active within the CG community of late.

I'm curious as to whether there are other ideas on what areas are likely to push CG forward over the next five to ten years.
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Monday, March 27, 2006

Stanislaw Lem has passed...

One of the most creative science fiction writers I have ever read, Stanislaw Lem just passed away. His writing was prescient, mind-bending, and often hilarious. His ability to write absurdist masterpieces was akin to Philip K. Dick, but without the gloomy darkness. If you read nothing else of his work, do read the Cyberiad, and his meditations on Golems that predate Ray Kurzweil and the Singularity by decades.

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Monday, March 20, 2006

Job posting.

It is a recurring problem that my blogging activity and research activities are inversely proportional. I am trying to fix this though. In the meantime, a job announcement for those of you interested in algorithms work on the wild fringes, where the data is twice the size and has claws ten times as sharp:
AT&T Labs - Research has an opening in our Internet and Network
Systems Research Center. One of our needs is in the general area
of algorithms, data structures, optimization, and discrete mathematics
and we are looking for active PhD researchers in these areas who also
want to have an impact on the real world. To see the researchers we
currently have in these areas, go to

http://www.research.att.com/~dsj/algs/people.php

Interested potential candidates should upload their resume to our website

http://www.research.att.com/academic

and let David Johnson (dsj AT research DOT att DOT com) know that they have done so.

AT&T is an Equal Opportunity Employer.
Categories

Friday, March 03, 2006

It's...

The Monty Python method for generating random variables:

Many methods have been developed in the past—see, for example, the comprehensive book by Devroye [1986]—and methods are usually given names to identify them. I, Marsaglia, called this the Monty Python method when it was developed, some 20 years ago, because opening graphics on the British television show Monty Python’s Flying Circus resembled the essential element of the method. The zany Monty Python crew pictured a stylized head with a hinged top that folded open, with all kinds of silliness pouring out. The Monty Python Method has an analogous hinged top that is folded over to suggest, among other things, an interesting way to generate a random variable. You may judge for yourself its silliness.
Categories

Adversaries

David Molnar has an excellent article on the hidden assumption behind cryptography. In listing this assumptions he also hits upon some of the core contributions of theoryCS.

The first is a robust formal definition of efficiency, or tractability. In fact, the idea of a "reasonable" computing model works very well in cryptography, where ever since the days of RSA, the game has been to prevent attacks by a limited adversary, rather than an allpowerful one (which would be much harder).

Which brings up a second core contribution; the idea of worst-case performance, and an adversary that can do anything. One thing that I've often noticed when working with people in other areas is that they are surprised when I can prove that such-and-such technique is optimal, or approximately optimal, or efficient. The power of worst-case analysis is in the ability to make such sweeping guarantees, and it's so ingrained into our psyche that it can be surprising to have some one else note this explicitly.

But worst-case analysis has its limits, and David alludes to this with his question on why anyone would ever assume that an adversary was not worst-case:
This assumption makes fields that assume some kind of distribution on inputs or on errors seem extremely strange. Electrical engineering does this in the context of coding theory, and it's also common in statistical learning theory. These fields have enormous practical impact and relevance, which I acknowledge and appreciate. I just have a hard time with the shock of "well, why do we believe errors must be distributed like that?"
In fields like game theory and cryptography, your adversary is assumed malicious; this is often true, especially code hackers, and is a good modelling assumption (think "selfish agents" and the like). Theorems proved here are "pure"; you start off with a set of assumptions about your world, and the results have guarantees within this world.

But when you start getting into areas like machine learning, data mining, and data modelling in general, your "adversary" is Nature, or some unknown indifferent process that generates data. Time and again we see what we would formally think of as heuristics work very well "in practice" and often the explanation is that the algorithm is able to exploit some property of the data (something we can then prove after the fact). Whether it's expectation-maximization, its cousin k-means, ICP, or even the simplex method, we see the same story over and over again.

Worst-case analysis, applied straight up, does not help us in these domains. Worst-case analysis often provides bounds that are weak, and algorithms that are ineffective on many kinds of data sets. To use formal methods, you need to dig deeper into a problem, and try to understand the data sources themselves, and often you come up with hidden structure that can be exploited formally.

I can answer David's question by going all the way back to Gauss. According to Leonard Mlodinow, it was when Gauss was overseeing a surveying project that he discovered that the errors in measurement followed a bell curve (hence, Gaussian distributions). The central limit theorem tells us that all kinds of i.i.d error will end up looking Gaussian after a while. Many natural processes also generate power law or log normal distributions. The point is that if you're dealing with nature, then more often than not you're dealing with data that is stochastic rather than adversarial, and modelling it as such gives you a better handle on algorithm design.

Thursday, February 23, 2006

Fractal cornrows

So all this while, Muthu was really making nonverbal statements about the fractal nature of the universe.

Categories

Friday, February 17, 2006

Chazelle throws down the gauntlet

From physorg.com:
..mathematics produces the equivalent of one-liners – equations that are pithy, insightful, brilliant. Computer science is more like a novel by Tolstoy: it is messy and infuriatingly complex. But that is exactly what makes it unique and appealing -- computer algorithms are infinitely more capable of capturing nuances of complex reality in a way that pure mathematics cannot.
Read the whole interview. I don't know about Einsteins of computer science: arguably we've already seen fundamental tectonic shifts in the way we think about theoryCS. But it is telling that some of the most bedrock developments in algorithms came way before computers were fashionable; the whole of the 70s was a golden era for the study of basic algorithms. It makes this quote seem oh-so-true, and yet tragic, in that we are still trying to make an argument that we've lived and breathed for so many years.
Theoretical computer science would exist even if there were no computers.
The more I think about this line, the more I appreciate its deceptive subversiveness. In one line, it turns on its head most of the received understanding about the nature of computer science and the nature of algorithms. How indeed could theoretical computer science exist without computers ? This statement can only make sense once you realize that that the theory of computation is not about computers, but is about the process of computing, about deduction and formal reasoning, and is fundamentally about efficiencies; how quickly, how succintly, how accurately ?

The confluence of computer science and programming has brought our field much riches and much attention, and for that we should be grateful. But it is time for our field to take its rightful place as the language of quantitive and effective science, as Bernard rightly puts it.

(HT: Neighbourhood of Infinity)

Update: Bernard kindly points me to an essay that expands upon the things he says in the interview. It's a freewheeling ride that smacks of crazy guitar riffs and strange rhythms. Don't believe me ? Read it for yourself. Here's a sampler:
Moore's Law has ruled the roost for the last 40 years. All the oohs and aahs you hear about the digital revolution are nothing but the squeals humans emit when tickled pink by Moore's Law. From the nice (medical imaging, e-commerce, whole-genome sequencing) to the vital (Xbox, IM, iPod), its rule has been a veritable ticklefest. Moore's Law has been the sizzling cauldron in which savvy cooks have whipped up a dazzling variety of tasty dishes. Without it, the Information Superhighway would be a back alley to Snoozeville; the coolest thing about a computer would still be the blinking lights.
Update II: Lance and Ernie weigh in as well.

Categories

Thursday, February 16, 2006

A message from the TCS funding committee

Via Sanjeev Arora, a note from the TCS funding commitee. A modified version of this will appear in the March issue of SIGACT News. A summary:
  • There will be a call for proposals in the NSF theory program this spring and grant sizes are expected to be larger than before. So please apply and send good proposals.
  • The report outlines things you can do to help improve funding for TCS (please read and act upon). It also describes initiatives launched by the Karp committee to help bring more funding to TCS.
  • Please feel free to forward this email to all interested parties. We have also started a new moderated mailing list tcs-funding (which will automatically cc to the older theory-advocacy list). Posts are allowed on this list only by permission (guaranteed to be spam-free; only news related to grants and funding).

Categories

Wednesday, February 15, 2006

And it's OUT !!!!

54, count 'em, 54 juicy sausages at the 2006 sausage fair in Sedona. Alas, I submitted a hot dog.

Some notable noteworthies:
  • (discussed earlier) Minimum Weight Triangulation is NP-hard. Wolfgang Mulzer, Guenter Rote.
  • On the worst case complexity of the k-means method. David Arthur, Sergei Vassilvitskii. They show an exponential lower bound for the convergence of k-means. An intricate and interesting construction.
  • On the ICP Algorithm. Esther Ezra, Micha Sharir, Alon Efrat. This paper analyzes a rather well known algorithm for the registration of point sets, the so-called "Iterated Closest Pair" or ICP algorithm.
It's worth noting that the latter two papers are both about a rigorous analysis of well known heuristics. Sariel has more notables.

Usual disclaimer: I hold no grudges against papers not mentioned. There are only so many hours in the day :). Am happy to mention papers that others find noteworthy: use the comments or email me.

Update (2/16): 142 papers were submitted.

p.s for those not in the know, if you say SoCG fast enough, it becomes 'sausage'.

p.p.s For Mr Googlebot, "SoCG 2006 accepted papers".

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Tuesday, February 14, 2006

Latest Baez

Is up, and this time it's on complexity theory ! It even contains a post-within-a-post, by Scott Aaronson. Baez covers crypto and pseudorandomness, and has a ton of pointers as usual. The most hilarious link:
From their home page:
...researchers can't just "think" of deterministic numbers; the human brain is an incredibly complex system that is poorly understood. In addition, medical research shows that our brains can be influenced by electromagnetic radiation, including cellular phones and even microwaves. It obviously wouldn't do to have important issues of national security corrupted by stray radio waves! Luckily, computers can help us solve this problem.



Categories

Monday, February 13, 2006

Concentration of Measure

Devdatt Dubhashi and Alessandro Panconesi have a first draft of a monograph on concentration of measure, essentially the study of tail bounds for random variables: given a random variable X, how does it deviate from E[X] ?

Their goal is to write a "user-friendly" guide to measure concentration. From the preface:
Our main goal here is to give an exposition of the basic methods for measure concentration in a manner which makes it accessible to the researcher in randomized algorithms and enables him/her to quickly start putting them to work in his/her application.
The book starts with the basic Chernoff-Hoeffding bounds and variants. It then delves deeper into "more recent" technology like Azuma's inequality, martingales, the method of bounded differences, and more. Talagrand's inequality comes next, followed by the log-Sobolev inequality.

What the draft does really well is connect the dots between the techniques and how they are applied. With exercises, problems, and worked-out examples, it is an excellent text for a course, or even as a companion text in a course. I should add that it is very well written; balancing exposition and rigor at the level that I like (your mileage may vary).

It's a book that's really needed. There are a lot of sophisticated methods for analyzing tail bounds, and a text written like this can potentially make martingales and Talagrand's inequality the kind of as-natural-as-breathing analysis tools that Chernoff bounds currently are.

Now I can only hope the authors manage to finish the draft. Maybe if you like the manuscript you should email them with encouragement !


Categories

Grants.gov

USACM discusses a Washington Post article about the new Grants.gov system for viewing and filing funding applications. Apparently the new system requires you to download a client program to view and submit applications. The kicker is that this is a Windows-only app; they recently started using Citrix as a way of dealing with this problem, but there are still no clean solutions.

The Washington Post article explicitly refers to Mac users (because of the preponderance of Mac users in the natural sciences, I imagine), but the problems remain for Linux users as well. I have never had to use this system, and since the NSF allows for submission via FastLane as well, I doubt many of my readers have, but I find it rather amazing that the government felt the need to design a special application just to allow researchers to connect securely to the main funding servers.

Update: Dave Schroeder of UWisc says:
The University of Wisconsin has released a standalone package for using Grants.gov on Mac OS X as a service to the community. The package uses Citrix client software and a special settings file to access the central Citrix server provided by Grants.gov, allowing users to access and use the PureEdge software via the remote Windows machine running Citrix server software:

http://apple.doit.wisc.edu/grants.gov/
Categories

Wednesday, February 08, 2006

String theory and NP-hardness

Via Peter Woit, a paper that proves the NP-hardness of a problem relating to the (in)famous string theory "landscape". Specifically,
We study the computational complexity of the physical problem of finding vacua of string theory which agree with data, such as the cosmological constant, and show that such problems are typically NP hard.
I mention this because it appears to be among the first few examples of NP-hardness impinging on the frontiers of physics. The paper has a very lucid explanation of some of the places in string theory where NP-hardness and other complexity notions pop up.

Some skepticism as to the relevance of this proof, here.
Categories

Tuesday, February 07, 2006

February is the cruelest month

I was recently grumbling about conflicting deadlines: conference A announces results well after conference B submission deadline has past. STOC and SoCG have an ongoing conflict that I have always felt "conflicted" about. In fairness though, with the number of conferences just in the broad area of algorithms/theory, it's hard not to have conflicts. This got me thinking though: exactly how bad are the collisions ?

I decided to make a somewhat ad hoc list of conferences in the general scope of algorithms and theory (i.e topics in this conference will often show up in STOC/FOCS/SODA), and look at their submission deadlines (a man's got to do something while waiting for his sausage...). The resulting timeline is reproduced below; the blue bar indicates the span of time from submission to result announcement, and the red dot indicates the actual date of the conference.

It is not surprising to see how academic schedules appear to influence conference scheduling (travelling in the summer is so much easier), but I did expect to see a slightly more equitable distribution of deadlines over the year. Indeed, February is the cruelest month.

Notes and caveats:
  • I used the most recent conference dates; there are variations from year to year, but not significant ones.
  • WADS and SWAT are really the same conference, but alternate.
  • RANDOM and APPROX operate together
  • I wonder why ISAAC and FSTTCS, which are both Asian theory conferences, schedule themselves to collide that way.
  • As some pointed out, these are not conflicts per se; the number of people submitting to (say) COLT and CPM at the same time is probably small. I was more intrigued by the density of deadlines in the early part of the year.
Not only does most travel happen in the summer, I imagine that much research must happen then as well. It's a good time to get manuscripts ready before the fall onslaught begins.


Categories

Sunday, February 05, 2006

Welcome To The Machine

S. Muthukrishnan, also known as Muthu, also known as the person who knows everyone in theoryCS*, has decided to eat some pizza. Welcome !!!



* A little known corollary is that if Muthu doesn't know you, you may not actually exist.
Categories

Thursday, February 02, 2006

I didn't realize finding airfares was that hard.

But it does make me feel a lot better. From a talk announcement over at [LB,UB]:
At any moment there are between 2,000 and 10,000 commercial airliners in the sky, part of a dense network that provides, for example, more than 100,000 practical paths from Boston to the San Francisco area every day. At its core, finding a sequence of flights that meets the user’s stated time constraints is a path-planning problem which can be solved with well-known techniques. But the airfare search problem is much more complex than that. In fact, the airlines’ price structure is so rich that finding the cheapest price for a simple round-trip journey is in the general case provably undecidable. Even if one bounds the size of solutions to a small number of flights there may be more than 1020 reasonable answers to a simple travel query. The problem is compounded by the fact that airline revenue management systems are constantly and dynamically adjusting the prices for each flight along a discretized scale.
Seriously though, how is this even possible ? There are a finite number of routes at any given time, and i am assuming that no one pays me to fly (I'm ignoring voluntary bumps of course), so the total path length must increase if I take longer and more byzantine routes...

Update (2/3): Michael Mitzenmacher indicates that there is more to the problem that meets the eye. In fact, he goes further:
If you have any smart students who are looking for a job in a "real-world" company, I'd strongly recommend they look at ITA software. Obviously I've drunk the Kool-Aid, but I think they'll continue to be an innovative, leading company in the travel space. And heck, how many companies do you know that even think to advertise themselves by giving a talk about the undecidable problems they are tackling!


Categories:

STOC Numerology

Via Piotr via Sariel, I hear that there were 288 submissions to STOC this year (and 78 accepted), making a net acceptance of rate of 27.1%. Comparing this to Jeff's charts from last this year, it looks like both submissions and acceptances held steady.
Categories

Monday, January 30, 2006

STOC 2006 results out

List of papers here.

Some quick notes on seeing the papers:
More to (hopefully) come as I peruse the list.

Update: 1/31/06: Sariel points out two more interesting papers:
  • Searching Dynamic Point Sets in Spaces with Bounded Doubling Dimension - Richard Cole and Lee-Ad Gottlieb.
  • A Quasi-Polynomial Time Approximation Scheme for Minimum Weight Triangulation - Jan Remy and Angelika Steger.

    This one is particularly interesting in the light of the new NP-hardness result for MWT by Mulzer and Rote. A quick glance at the above paper indicates that they use a technique akin to the method used by Sanjeev Arora, and Joe Mitchell, to solve TSP in the plane. You divide the plane into small pieces, consider the different triangulations in each piece, and prove a "structure lemma" that describes how the interface of almost-optimal solutions look. Since the algorithm runs in quasi-polynomial time, I imagine the next step is to see if it can be be beaten down to a PTAS.
Credit goes where credit is due. The geometry community often moans and groans about their neglect at the hand of STOC/FOCS committees. This time, there is really nothing to complain about; a lot of nice geometry papers have made it in.
Categories

Collaborative Mathematics and Kepler's conjecture/theorem

If the 1990s was the decade of the web, the 2000s might very well be the decade of collaborative methods, whether it be social bookmarking, tagging, or recommendation systems. A collaborative system we possibly did not anticipate is combined theorem proving.

Kepler's conjecture about the optimal packing of balls in 3D was finally proved by Thomas Hales in 1998. Or was it ? Since 1999, a 12-member review committee of the Annals of Mathematics has been going over the proof in order to verify it. The NYT reported nearly two years ago that there were problems in the verification process, and now we hear the details, on Thomas Hales' Flyspeck page:

Robert MacPherson, editor of the Annals, wrote a report that states

``The news from the referees is bad, from my perspective. They have not been able to certify the correctness of the proof, and will not be able to certify it in the future, because they have run out of energy to devote to the problem. This is not what I had hoped for.''
Interestingly, Gabor Fejes Tóth, the chief referee, wrote a report certifying that he was "99%" confident of the proof, but no more, and the editor therefore concluded that
it's not enough for complete certification as correct, for two reasons. First, rigor and certainty was what this particular problem was about in the first place. Second, there are not so many general principles and theoretical consistencies as there were, say, in the proof of Fermat, so as to make you convinced that even if there is a small error, it won't affect the basic structure of the proof.''
Apparently, the Annals will publish a paper on this topic with a disclaimer stating that the computer parts of the proof have not been verified. In the meantime, (and here's the collaborative aspect of this), Thomas Hales and others have undertaken a joint effort to rewrite his proof in a computer-verifiable form using OCAML. The project is called Flyspeck, and the page contains information on how to "participate" in the proof:

The first step is to learn the relevant background material:

  • Objective CAML,
  • HOL light, and
  • the idea of the proof of the Kepler Conjecture.
See the resources listed at the bottom of the page for more information about these topics.

The second step is to become an experienced user. In practical terms, this means being able to create your own proof in the HOL light system.

If you have successfully proved a non-trivial theorem in the HOL light system, then contact Thomas C. Hales (http://www.math.pitt.edu/~thales) if you wish to participate.

(HT: sigfpe)

Sunday, January 29, 2006

PIR and turning the tables on the NSA

My previous post on PIR generated some interesting comments on the practicality of such schemes and why Google isn't already doing it. An angle to this that I should have mentioned earlier is the way that PIR-like methods can actually help government snoopers.

David Molnar had pointed to this a while back: it's a paper by Ostrovsky and Skeith from CRYPTO 2005 titled 'Private Searching on Streaming Data'. The premise is that you are the NSA or some other intelligence organization, and you want to run searches on various data streams without any adversary being able to detect what your searches are about (presumably so that they can't game the system to avoid detection). This of course is the same as the PIR paradigm, except with the "good guys" and "bad guys" flipped around.
Categories

Thursday, January 26, 2006

Comments RSS feed

Since Blogger continues to ignore my plaintive requests for the most useful feature any blogging software can have, I made a hack based on suggestions made elsewhere.

If you'd like to subscribe to a comment RSS feed (if you posted a comment and want to know if there were any responses, this is particularly handy), throw this link into your blogreader. It's not has snazzy as the kinds of feeds my wordpress brethren can generate (the feed is not separated by post, for example), but it's handy. Of course, if you always read this blog directly on the web and/or don't know what RSS is, ignore this message.
Categories

Wednesday, January 25, 2006

Food for thought.

sed -e 's/physics/computerscience/' <
I think it would actually be healthier for theoretical physics these days to take a look at how mathematicians operate, because mathematics has always been a less faddish subject. In mathematics there is much more of a culture where people spread out and devote their lives to thinking hard about something that interests them. There has always been much more of a culture in physics that you want to work on something where you can get results and produce a paper a few months from now. And when the problems are very hard and no one knows what to do, I think people need to be willing to dig in and spend years thinking about something different than what other people are thinking. And there really isn't the kind of institutional support within the physics community for this kind of behavior, whereas there is in mathematics.
Hits close to home, methinks...

(Source: Discover Magazine interview with Not Even Wrong proprietor Peter Woit)
Categories:

Private Information Retrieval

Google, MSN and Yahoo were recently served with subpoenas for search data from their databases. The background, from an article by Columbia professor Tim Wu in Slate:
Back in the 1990s, Congress passed a succession of laws designed to keep porn off the Internet. Those laws didn't work—largely because the courts kept striking them down as violations of the First Amendment. Sick of losing and finding themselves back in the district court defending a reconfigured version of the anti-porn bill (now named the "Child Online Protection Act"), lawyers in the Justice Department decided to hire Berkeley professor Philip Stark. Stark's assignment: Use statistics to show what everyone already knows—that there's an awful lot of porn on the Internet.

Stark's plan is to demand that Google and the other major search engines supply him, and thus the government, with a random selection of a million domain names available for search and a million sample user queries. He will then demonstrate how truly nasty the Internet is, and in particular, just how hard it is to block out stuff that's "Harmful to Minors." Faced with this third-party subpoena, Microsoft and Yahoo! agreed to supply Stark with this information, but Google refused, calling the subpoena request "overbroad, unduly burdensome, vague, and intended to harass."
He goes on to make the point that the problem is not that Google et al were slapped with subpeonas, but that they had the data lying around in the first place. His suggestion: get rid of tell-tale information:
That's why the public's demand must be of Google—not the state. It should be that Google please stop keeping quite so much information attached to our IP addresses; please modify logging practices so that all identifying information is stripped. And please run history's greatest "search and delete," right now, and take out the IP addresses from every file that contains everyone's last five years of searches.
Coincidentally, I was chatting with Piotr Indyk the other day at Penn, and he made the very valid point that in a sense, theoretical computer science is already on the case, and has been studying this problem for a very long time. The field of private information retrieval is precisely about this:

Can you make queries from a database without the database knowing what you want ?
It seems impossible (if you don't already know the answer). But here's a silly solution:
Ask for all the data from the database ! There's no way the database will know what you really wanted.
The solution is indeed silly, but why exactly is it ? Well, because you'd need to extract all the n bits of information from the database [1] to get the answer bit [2] for one query So if we think of "stuff the database returns" as a bounded resource, can we do better ?

Well, as you might have guessed, if you want to be deterministic, then not really. But if you can toss coins when asking your queries, while still guaranteeing that the answer is always correct,
and if you assume that you are really querying multiple non-communicating copies of a database (not so unrealistic), then you can do a lot better. For example, if you wanted to know the value of a single bit (the "query") of a string of n bits (the "database"), you could pick a random subset of the string, and ask the first database for the XOR of the bits. Then XOR the index you want with the set, and ask the second database for a similar XOR. You can XOR the two answer to get your bit, and the databases are none the wiser.

Now this really doesn't save you much, since you'd send n bits in total (on average) to the servers, but the scheme can be generalized to k servers, in which case you'll end up with a total transmission of something like k log k n^(1/log k), which is significantly sublinear.

There are many variations: how smart can the servers be at trying to decipher your answers ? (in the above example, even an all powerful server can't do a thing) ? How much can the servers talk to each other ? what kinds of queries can you ask ? and so on.

One might argue that assuming the servers can't communicate with each other is an unreasonable restriction. Not so really, especially if you consider that it might be in Google's interests to facilitate this kind of querying [3]. Another interesting question that I don't think has been studied would be: can you construct effective link graph structures and search results without needing to retain any information about the pages themselves ?

Piotr made the interesting point that there's a lot of scope here for a company that wants to innovate in the search space: "Search with our engine! We have no clue what you're looking for, and we'll find it anyway!". In fact, there's a web page on practical PIR maintained at the Institut für Informatik at the Humboldt-Universität zu Berlin by Prof. Johann-Christoph Freytag and Dmitri Asonov.

Since the business of theoryCS these days is PR, it's worth pointing out that privacy is rapidly becoming a major area of concern, and work springing out of theoretical computer science is ideally placed to have an impact here. Just sayin'....

I drew my sources from the wonderful survey on PIR written by Bill Gasarch (who's current guest blogging at the Complexity Blog) for Lance Fortnow's Complexity Column. He also has a companion web page, and the two are a valuable resource of information on this topic.

(HT: BoingBoing)


[1] Theoretical computer scientist love referring to all sizes as 'n'. If there are more, we will often use 'k', 'm', and the often scorned 'U".


[2] The one thing we love more than calling things 'n' is designing questions with YES/NO answers.


[3] There is another post waiting to be written on why it's NOT in Google's best interests to help make private information retrieval a reailty. Such a post would have a heavy dose of phrases like "Web 2.0", "AdSense", "AdWords", "revenue streams" and "targeted search" and would bore everyone to tears.

Categories:

Tuesday, January 24, 2006

SODA Day III.

I will attend more talks next year...
I will attend more talks next year...
I wil attend more talks next year...

The morning session talks were moved from their original location because of flooding in the conference room. No, I am not making this up.

So we reach day 3, and by now most people have given up the pretence of attending talks. Alan Frieze's invited lecture on random graphs was packed though. Most of you probably know what random graphs are: briefly, imagine a graph generated by adding an edge between any pair of vertices with probability p.

There are all kinds of interesting properties one can prove on random graphs. One of the most striking is a sharp "phase transition" that occurs in connectivity, going from a mostly disconnected graph to a connected one, as p gets large enough (slightly larger than log n/n). Random graphs have become a useful way of modelling the Web graph: for example, the preferential attachment process of Barabasi and Albert defines a random graph whose degree sequence follows a power-law, and that mimics many properties of the Web graph.

This was probably the most technical of the three talks, and had (at least hints of) some seriously cool methods in probabilistic analysis. I'll link to the talk when it comes online.

Outtakes:
  • One of the "pitfalls" of being known as the geomblogger is that when I sit down with my laptop, the default assumption appears to be that I am blogging about the conference.

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Monday, January 23, 2006

SODA Day II...

Today's invited talk was by Princeton's Larry Peterson. He spoke about the aging of the Internet, and how it can't quite cater to the demands of today's world. One of the challenges of adapting the network is the legacy problem: as he put it, it's hard to convince Cisco to change the interpretation of one bit in their routers.

One of the issues that seems critically important in the internet of today is the issue of control. The original internet grew "under the radar". Developed primarily by researchers and technologists, its governing principles were constrained by technical, rather than political, considerations. The next generation of the internet will not have this luxury, and the brouhaha over ICANN is a tiny indicator of the kinds of battles likely looming. Interesting times...

Jeff Erickson did an admirably thorough stream-of-consciousness rendering of the business meeting, which I won't try to duplicate. There was no beer; absolutely none; nada; zilch; not a drop. Everything seemed pointless and arid after that....

I will say this: I continue to be amazed at the capacity of the theory community to repeat the same arguments on the same topics year after year, while presenting said arguments with the kind of gravitas that suggests deep thought and contemplation. Maybe that's how we write so many papers. This year's topic du jour was the always-delightful "submission size formatting" discussion (one of these days I should make separate pages for each of these annoying arguments, debunking all the annoying comments that everyone makes).

Am I irritated ? of course not; my mouth is strangely dry though. Oh yeah, there was no beer.

It was interesting to see Cliff Stein's list of the most active topics at this conference; there were the usual suspects like approximation algorithms, graph algorithms, and computational geometry, but game theory made a (somewhat) surprising appearance in the top five. In retrospect, this is not surprising, especially when we consider things like the minimax theorem, and the fact that most of theoretical computer science consists of games played against an (often unbounded) adversary. The last few years have seen a steady increase in the number of game theory papers in STOC/FOCS/SODA, and this trend will likely continue.


Categories:

Sunday, January 22, 2006

SODA II: Predictions....

Today's highlight was the invited talk by Rakesh Vohra titled 'Predicting the Unpredictable'. It starts from the following very simple questions:

Given a generator that's producing 0s and 1s, your goal is to predict the next bit. You don't know anything about the generator, and you have to make some prediction. The measure of your performance is the asymptotic fraction of predictions you make that are correct.
An amazing result is that if the number of 1s in the output thus far is hn, you can come up with a randomized scheme that achieves max(hn, 1-hn) -eps. This result was proved in 1957 by James Hannan, and has apparently been reproved 13 times !

If you think of 1 as "it will rain tomorrow", then you see why this is an important problem. Of course, weather forecasters usually predict with a probability: there is a 20% chance of rain tomorrow. How do we evaluate the effectiveness of a prediction in that case. The answer is quite elegant, and is called "calibration". The idea is that you look at the subsequence of 0s and 1s where the forecaster predicted a 20% chance of rain, and check if over this sequence, there was indeed a 20% fraction of rain. Repeat for all probability predictions, weighting by the length of the subsequence.

A stunning result is that no matter what measure of discrepancy you use, and what kinds of subsequences you pick, it is possible to design a strategy that drives the calibration error to zero. In other words, a completely clueless weather forecaster might be a perfect predictor under this measure. Rather disturbing...

In the afternoon, there was an interesting talk by Seshadri Comandur on self-improving algorithms. The idea is that as an algorithm, you want to learn from the input, and then be able to generate answers that are optimal with respect to the distribution the input is being drawn from (think of this as a generalization of average-case analysis). Notice the similarities between this work and the invited talk; here also, you want to adapt your behaviour to the input so that you are optimal for the distribution it comes from.

Outtakes:
  • If you walk out of a skywalk, thru a parking lot, down the elevator, thru the parking lot, via tunnel, you can actually find somewhat passable Starbucks-branded coffee. Trust me, it's worth the walk :)
  • Jeff Erickson once again has his business meeting drinking game. I have to say that it's so complicated, I'll need to print out a sheet with all the rules, and will probably forget them once I get drunk enough...
  • Maybe that's the point...
  • Can you get drunk before the business meeting ? By my count David Eppstein needs to take 6 drinks for his hotel complaints, plus a special bonus for his innovative complaint about airplane noise at 1am. I myself am at about 3 drinks...

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