Category: Meta

The hunch.net server has been updated. I’ve taken the opportunity to upgrade the version of wordpress which caused cascading changes.

1. Old threaded comments are now flattened. The system we used to use (Brian’s threaded comments) appears incompatible with the new threading system built into wordpress. I haven’t yet figured out a workaround.
2. I setup a feedburner account.
3. I added an RSS aggregator for both Machine Learning and other research blogs that I like to follow. This is something that I’ve wanted to do for awhile.
4. Many other minor changes in font and format, with some help from Alina.

If you have any suggestions for site tweaks, please speak up.

Iain noticed that hunch.net had zero width divs hiding spammy URLs. Some investigation reveals that the wordpress version being used (2.0.3) had security flaws. I’ve upgraded to the latest, rotated passwords, and removed the spammy URLs. I don’t believe any content was lost. You can check your own and other sites for a similar problem by greping for “width:0” or “width: 0” in the delivered html source.

If you have been disappointed by the lack of a post for the last month, consider contributing your own (I’ve been busy+uninspired). Also, keep in mind that there is a community of machine learning blogs (see the sidebar).

It’s been almost two years since this blog began. In that time, I’ve learned enough to shift my expectations in several ways.

1. Initially, the idea was for a general purpose ML blog where different people could contribute posts. What has actually happened is most posts come from me, with a few guest posts that I greatly value. There are a few reasons I see for this.
   1. Overload. A couple years ago, I had not fully appreciated just how busy life gets for a researcher. Making a post is not simply a matter of getting to it, but rather of prioritizing between {writing a grant, finishing an overdue review, writing a paper, teaching a class, writing a program, etc…}. This is a substantial transition away from what life as a graduate student is like. At some point the question is not “when will I get to it?” but rather “will I get to it?” and the answer starts to become “no” most of the time.
   2. Feedback failure. This blog currently receives about 3K unique visitors per day from about 13K unique sites per month. This number of visitors is large enough that it scares me somewhat—having several thousand people read a post is more attention than almost all papers published in academia get. But the nature of things is that only a small fraction of people leave comments, and the rest are essentially invisible. Adding a few counters to the site may help with this.
   3. Content Control. The internet has a huge untapped capacity to support content, so one of the traditional reasons for editorial control (limited space) simply no longer exists. Nevertheless, the time of readers is important and there is a focus-of-attention issue since one blog with all posts on all topics would be virtually useless. In an ideal world, the need for explicit content control would disappear and be replaced by a massive cooperative collaborative filtering process. This shift is already well underway since anyone can start their own blog and read anything they choose. Tighter integration of collaborative filtering into the overall process will surely be useful. I’ve reorganized my links to other blogs to make this a little bit easier. In the last couple years, many new machine learning related blogs have started (just recently: Yee Whye’s), which is great in several ways.
   4. Difficulty. Talking clearly about things you barely understand (and no one else does) is simply very difficult. Expending the effort to write clearly about them in a post is not too difficult from expending the effort to write clearly about them in a paper, which is the traditional mechanism of publishing. There is no simply way around this problem, although changing people’s expectations may be helpful. Right now, the expectation in academia is (partially) set by the academic paper. A different expectation, more akin to the way we discuss problems with each other in person, may be helpful.

   For the record, I’m always happy to consider posts by others. If you are considering your own blog, trying a guest post or two is a great way to experiment. Many people don’t have the time or inclination to run their own blog, so guest posts are essential.

2. What is a good post? A good post is fundamentally an interesting post, but “interesting” can be broken down further.
   1. Speak plainly. The review process in academia can sometimes favor the convoluted over the plain. A blog strongly encourages otherwise since the backgrounds of readers are very diverse. If you aren’t self-editing for simplicity, you aren’t being simple enough.
   2. Believe in it.
   3. Lack of comments is not always lack of interest. As an example the posts of the form “interesting papers at <conference>” tend to get very few comments, but they are some of the most viewed.
   4. Avoid duplication. The most obvious way to use a blog is as a mechanism for posting finished research. It’s ok for this, but the most interesting way of using the blog are for topics which could not be stated as a research paper.