Wednesday, September 17, 2008

Small Steps...

Every once in a while, I see a blog entry or comment with the lament that the CS publishing model is just wrong. The common statement is that the conference-oriented publishing approach leads to incremental, trivial papers, solving problems that are easy instead of the "real" problem.

I'd like to offer a contrasting opinion, one I've stated before, but may be new to some. (And since the criticisms above are repeated cyclically, I don't see why I can't repeat my response.)

Having worked some in the area of heuristic algorithms, I've gained a healthy respect for the fundamental approaches of repeated refinement, parallelization of efforts to explore a search space, and the occasional bit of random wandering. Greedy-style heuristics don't get to good answers by big jumps, but a multitude of small steps. Parallelization, leveraging the power of crowds, greatly speeds up such heuristics, and frequent communication between the agents working in parallel helps move everything along. And most good heuristic algorithms require a bit of a random (or explicit!) push to keep moving through the space of possibilities, to find new parts of the search space to yield better solutions than the already plumbed over areas.

The CS conference publication model shares these features. Yes, there are many more small steps than big jumps. Yes, there are times where less fruitful and interesting directions are explored. But the community as a whole moves rapidly, churning through ideas and, I think, rapidly focusing on promising ones. Also, new ideas and directions arise with, I think, remarkable frequency. Looking at any single conference, you might think over 90% of it is junk -- or, at least, no so important in the grand scheme of things. And you'd probably be right.** But that doesn't a priori mean the conference publishing system is broken, and any argument that it is based on such reasoning doesn't even start to convince me.

This doesn't mean that we are excused from having taste and opinions as to what constitutes good work. Indeed, without this, we'd lack an evaluation function to lead us in the right directions. And I'm not saying the the contrasting "mathematics" style of publishing only fuller, complete papers is necessarily worse -- I don't think I've seen evidence one way or another. (I might admit to having a personal preference.) But if you want to argue the point, you need to do more than just look at individual papers in individual conferences, and focus on the whole.

[** A favorite quip from grad school that I still remember was when a systems friend told me "95% of theory papers are crap!", and I simply responded, "So that means we're 4% better than systems." Good times.]


Daniel Lemire said...

Some, like myself, who are very vocal about the problems do not worry about incremental research.

It is silly to sit in your basement for 10 years hoping for this big breakthrough.

Publish early and often.

Jonathan Katz said...

Overall, I agree with you. But I would like to throw out the following hypothetical question: Say there were no external pressure to publish. How many fewer papers would be published, and how much better or worse off would we, as a community, be?

Michael Mitzenmacher said...

Jonathan --

I'd say with no external pressure to publish, there'd be fewer publications. And my take, from my reasoning above, is that we'd actually be worse off (in terms of overall output) because of it. Although, to be sure, I wish I had more tangible evidence available.

Josh said...

I'd just like to point out that the alternative publishing model I mentioned on Mihai's blog -- the one used by math -- doesn't do away entirely with conferences. Mathematicians hold conferences all the time. I don't think there is less dissemination of information within the math community than within the TCS community. But it's virtually impossible for a mathematician to base their reputation mostly on conference publications (excluding cases where the conference publication was, say, a proof solving a million-dollar problem).