Escape

I just learned of a conference called ESCAPE (International Symp on Combinatorics, Algorithms, Probabilistic and Experimental Methodologies), to be held in China. The conference website has beautiful pictures, including my favorite water. I don't know if bosses like to sponsor their employees going to ESCAPE, but I can imagine the interview at the border control when I return. "Where were you?", the Immigration Officer. "I went to ESCAPE", me. I remember when I traveled to the FUN conference and the passport control officer in Italy asked what I was going to do in Italy.

Books around us

On a half a block walk to the subway in the morning, I find a streetside book vendor carrying an esoteric collection. It includes outdated books on TCP/IP, Oracle suites, and Media tools for Macs, most printed before 2000. These volumes have dense text, technical jargon, block diagrams, glossary lists, all pointing to a sense of purpose, sense of value. The vendor who carries Gunter Grass, LPs and fragances besides, must think, "Surely someone must find these volumes useful." Alas.

A typical subway ride for me is short. I can't look far within the 3 ft X 3 ft personal space I get in the crowded train. Still, I catalog the reading material around me, newspapers folded into readable squares and books showing remnants of the dogears. This morning I saw a Tolkien, a Paulo Coelho (the only good book he wrote, ie., The Alchemist) and a book of not-so-easy Sudoku's. I idle my time doing a Sudoku, my trail randomly crisscrossing the trail of squares filled by the owner of the book who is busy with a pencil and an eraser.

For Friends

Arnaud Sahuguet, the traveler, french-member-no-more at Bell Labs, swallower of miles without hiccups, told me that when I have braids, I put my head down slightly, and play with individual braids in the back of my head, testing each, pulling it, and moving on to the next. He told me it looks like I am lost in a zone, doing a calculation on the abacus. You have to be there to see it.

I went to a party to celebrate friends and their milestones. As I looked over at the Hudson river from the roof, with silent, lit boats plowing, and the NY skyline in view, Herve (this page has a picture more like him than that), in a moment of loose melody says, "Yeah, I swam the Hudson today." What an opening line for a conversation.

Here are some Suresh-esque references to geometry (thanks for the yank down the memory lane with his indian grad student post). I will combine that with my passion for Tennis:

- NY Times, no leader when it comes to sports pages, gamely tried to cover the US Open but gave in and talked about it in the Arts pages on Friday. A lovely set of excerpts from Michael Kimmelman's The Art of Tennis:

Tennis points, she said, are problem-solving equations for line drawings in space.
Translation: the beauty of the game is seeing, then trying to remember, the way a ball travels around the court during a point. Its path makes lines that arch, zig, move diagonally, straight, back and forth. The court is like a sheet of paper, with its own lines already drawn on it. Strategy entails mapping out and resolving combinations of lines — patterns — just as an artist maps a drawing.

- Maria Sharapova after the win at the finals:

"Well, I figured the last four times I have played against Justine I lost, so I thought I would just flip everything 360 degrees and do the total opposite," she said.

Off by a factor of 2.

KDD 2006

I went to the KDD conference at Philly. It is a mixed community with people from databases, data mining, statistics, applied mathematics and an occasional algorithmus. So, it is difficult to get a sense for central challenges, and the holy grail of open problems. The conference seems to have succeeded in turning people towards real data sets and public competitions with public data sets, which is encouraging. Andrew Moore gave a plenary talk: he was his usual engaging self with anecdotes of algorithms scalable to very large datasets with simple, elegant techniques, provable or not. I heard him first at a National Academy of Science meeting on data streams, and he continues to get great scalability. The industrial presence was strong: Yahoo, MSN and Google were firmly represented.

Main themes seemed to be privacy in data analysis, scaling and applying machine learning solutions to data mining, social network analysis like finding communities, and new data sources (blogs, wiki) and unique problems with them. The best student paper seemed to focus on speeding up Johnson-Lindenstrauss, a la, Achlioptas's work, but it was mainly heuristics and did not seem to refer to Ailon and Chazelle.

Btw, for contrast, I think SIAM Conf on Data Mining is less database-centric and draws more Statisticians and Applied Mathematicians, but that too may change.