How to make time for literature review

Answer: just wait until you're completely unmotivated to do anything else. Sunny days with perfect weather are really the only times I get a chance to do any significant literature reviews. This afternoon, when I was unable to get myself to stay in my windowless office, I (finally) sifted through the WSDM proceedings that I'm most interested in, and read a couple papers on trust/distrust propagation. I'm getting better at adding papers to my bibsonomy [rss]. The top 10 or so should be what I covered today.

Also a fun article: via Physics Arxiv Blog, To How Many Politicians Should Government Be Left? The article looks at the "efficacy" of a government compared to its cabinet size, and makes a rather nifty model of how opinions are formed in small networks. Another interesting bit is that while cabinet size ranged from 5 to 54, not a single government of the nearly 200 surveyed had a cabinet of size 8-- apparently it is common knowledge that that is bad luck, or something.

I also discovered that Jure was smart enough to submit last year's SDM paper to ArXiv, which yielded a citation. That has prompted me to register so I can post other publications.

This is related to a recent pet peeve of mine-- the fact that it's difficult to get conference proceedings. The ACM/Citeseer folks don't always things from workshops and the like that I'm interested in. Most authors have the sense to post their papers on their websites, but I much prefer being able to get a conference all in one place. Of course, professional organizations don't like to do that. I find it hard to believe that they really make money off of conference proceedings, so I can only guess that it has to do with publisher/copyright/legalities rules outside their control. Maybe someday CC/GPL will be able to wrest away some control.

ICWSM, semi-supervised learning

Returned from ICWSM, and was inspired to perhaps start blogging again, but we'll see how long that lasts.

The tutorial at ICWSM went well (pdf slides available at that link, ppt available by emailing me). I will be giving it again at NESCAI. There were a lot of great talks and posters at ICWSM; a lot more toward the text/sentiment mining side of things than last year, but still a great variety of concepts.

While in Seattle I missed the 10-601 class lectures on semi-supervised learning, and had to prepare a recitation anyway. So as part of that preparation I came across a good survey paper by Xiaojin Zhu. It has an entire section devoted to graph-based methods, some of which I hadn't heard of, so this was useful to me beyond giving me interesting things to talk about in recitation. It might be of use to try some of these algorithms on community detection in networks.