The CFP for the 5th IEEE International Conference on Data Mining is out. It will be held in New Orleans, Louisiana, USA.

The 2005 IEEE International Conference on Data Mining (IEEE ICDM ‘05) provides a premier forum for the dissemination of innovative, practical development experiences as well as original research results in data mining, spanning applications, algorithms, software and systems. The conference draws researchers and application developers from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, knowledge-based systems and high performance computing. By promoting high quality and novel research findings, and innovative solutions to challenging data mining problems, the conference seeks to continuously advance the state of the art in data mining. As an important part of the conference, the workshops program will focus on new research challenges and initiatives, and the tutorials program will cover emerging data mining technologies and the latest developments in data mining.

Paul Graham has done it again. He wrote a beautiful article on How to Start a Startup:

You need three things to create a successful startup: to start with good people, to make something customers actually want, and to spend as little money as possible. Most startups that fail do it because they fail at one of these. A startup that does all three will probably succeed.

I did start what one could call a startup and I failed. I did work like hell for a few short years. I made some good money, but all of it is long gone. However, I learned a lot.

One issue was that we didn’t have the right people. The other issue is that my love of money was not great enough. You’ve got to actually badly want to make money. All I wanted was to find a way to get paid to do interesting work.

These days, the money suck (a professorship is no way to make a living), but I pretty do what I like to do.

I think I still mostly want to be left in peace to my own ideas and work with collaborators I like. I think I’m succeeding at getting what I want. I will never become a big shot professor running a large laboratory (I would hate it), I will never become a filthy rich industry consultant (though I wouldn’t mind doubling my salary) because I will always pick contracts out of interest more than out of greed.

Lesson? I don’t know. Don’t listen to me, listen to Paul Graham and go start a startup, become filthy rich. It sounds like a great plan. I’m a lost cause.

Through Tall, Dark and Mysterious, I found this web page on How to Read Mathematics by Shai Simonson and Fernando Gouvea. This quote says it all:

Students need to learn how to read mathematics, in the same way they learn how to read a novel or a poem, listen to music, or view a painting.

Some of my papers are said to be “hard to read” because I make ample use of mathematical notations, even when it is not strictly needed. Some reviewers, though they won’t admit to it, don’t like my papers because they can’t read them. Of course, there is no shortage of Ph.D.s who can read mathematics, so there is no reason to stop using mathematical notations. To me, a paper with a strict adherence to mathematical conventions and a thorough use of mathematical notations is far easier to work with than a paper which tries to describe everything in English. English is an ambiguous and dangerous language, especially if you are not trained in philosophy and have English as your third language. Mathematics, on the other hand, is a true universal language and it can be extremely precise if needed. And that’s what I try to give my readers: a precise description of what is and what is not, not just vague impressions. I’ll keep the vague impressions for this blog.

Now, as of students, last time I taught Calculus, I was told that I was using too many Greek letters. Well, I didn’t apologize for using Greek letters. I probably kept using them. Students: learn to work with Greek letters, there is nothing wrong with them and if you do a lot of complex work, you’ll find that 26 letters are not enough and that borrowing from other alphabets does improve the clarity of your documents. Plus, there are some universal conventions you just can’t get around. I could say that “e” is a small quantity, but “e” is Neper’s number. So, when I want to refer to a small quantity, I use the Greek letter epsilon. So do at least another million of crazy geeks.

The real question is, when will I start using mathematical notations on my blog? That’s coming soon… I’ll get MathML on this very page in the near future. With plenty of Greek letters!!!

In the latest issue of SIAM Review (volume 47, no 1) (articles to be available online soon), I read a great paper for those who like mathematics and want a deeper understanding of how Google works. I knew how the PageRank algorithm worked, roughly, but I never imagined it was a true Linear Algebra algorithm. Of course, it is relatively simple as far as Linear Algebra goes, but still…

Gmail is a really smart email client. I found out it is even better than I thought. If you want to quickly find unread messages in your inbox, just search for “label:inbox is:unread”.

The trick also is to “star” the messages you want to come back to. This is much better than leaving them unread which is really a hack if you think about it. You build a todo list, always one click away.

Yuhong reacts to the paper Don’t Become a Scientist! by Jonathan I. Katz. Here’s what she had to say:

Whenever I met students who want to have a ph.d., I would ask them, do you really want it if I tell you the truth? Many students tell me that a scientist can be free to think anything and achieve what they think so that is the ideal life for them. But the truth is this career has too much harshness to be free. My Friend Daniel, a pessimist, has many posts recently about it. I agree with him on this issue though.

The paper she reacts to is also very entertaining. It goes after a few myths. One of them is that if you get a Ph.D. and finally do get a professorship, life will be great:

Suppose you do eventually obtain a permanent job, perhaps a tenured professorship. The struggle for a job is now replaced by a struggle for grant support, and again there is a glut of scientists. Now you spend your time writing proposals rather than doing research. Worse, because your proposals are judged by your competitors you cannot follow your curiosity, but must spend your effort and talents on anticipating and deflecting criticism rather than on solving the important scientific problems. They’re not the same thing: you cannot put your past successes in a proposal, because they are finished work, and your new ideas, however original and clever, are still unproven. It is proverbial that original ideas are the kiss of death for a proposal; because they have not yet been proved to work (after all, that is what you are proposing to do) they can be, and will be, rated poorly. Having achieved the promised land, you find that it is not what you wanted after all.

What can be done? I advocate that we inform potential students of the job prospects. Katz suggest we get funding agencies to stop funding so many Ph.D.s:

If you are in a position of leadership in science then you should try to persuade the funding agencies to train fewer Ph.D.s. The glut of scientists is entirely the consequence of funding policies (almost all graduate education is paid for by federal grants). The funding agencies are bemoaning the scarcity of young people interested in science when they themselves caused this scarcity by destroying science as a career.

I like his solution, but I’ve got no idea how I could ever have an impact on the policies of funding agencies. I’m not enough of a big cheese, but if you are, please help.

I conclude with this remark Katz made in his paper:

I have known more people whose lives have been ruined by getting a Ph.D. than by drugs.

This post makes the point that university professors are essentially self-organizing:

(…) universities are valuable primarily as the habitat of academic disciplines, whose self-organizing systems cannot be brought under central command. Bossing academics is like herding ants — creatures that are relatively feeble unless permitted to exercise their collective genius for self-organization.

So! That’s what universities are? Habitats for disciplines… Hmmm…