At the one year (+5 days) anniversary, the natural question is: “Was it helpful for research?”
Answer: Yes, and so it shall continue.
Some evidence is provided by noticing that I am about a factor of 2 more overloaded with paper ideas than I’ve ever previously been. It is always hard to estimate counterfactual worlds, but I expect that this is also a factor of 2 more than “What if I had not started the blog?”
As for “Why?”, there seem to be two primary effects.
- A blog is a mechanism for connecting with people who either think like you or are interested in the same problems. This allows for concentration of thinking which is very helpful in solving problems.
- The process of stating things you don’t understand publicly is very helpful in understanding them. Sometimes you are simply forced to express them in a way which aids understanding. Sometimes someone else says something which helps. And sometimes you discover that someone else has already solved the problem.
There are drawbacks which should not be minimized.
- A great deal of accumulated time and effort goes into writing posts.
- Stress. Telling coauthors “I’m sorry, but I don’t have much time to actually write.” is not at all fun. And the wrists are hurting.
One of the things that I thought would be a problem was running out of ideas for posts, but this just didn’t happen. I’m hoping to have more posts by others over the next year to help relieve (1). (Also, I often find the posts of occasional posters more interesting.) Problem (2) is just an ill of success that must be coped with.
- posts 1 every 2 days, on average (150)
- comments 3/post on average (492)
- posters 10
- registered users 72
- visits per day About 2000 (some uncertainty due to sharing of webserver with less-used sites).
- unique IP addreses per month Perhaps 7000 (uncertainty due to same source).
I’ve been surprised by the growth of traffic to the site. It is odd to realize that a post here is seen by more people than a talk at even the largest machine learning conference. Radically more effort goes into any talk at nearly any conference.
Please comment on any particular thoughts, suggestions, changes, for the new year or the last.
One part of doing research is debugging your understanding of reality. This is hard work: How do you even discover where you misunderstand? If you discover a misunderstanding, how do you go about removing it?
The process of debugging computer programs is quite analogous to debugging reality misunderstandings. This is natural—a bug in a computer program is a misunderstanding between you and the computer about what you said. Many of the familiar techniques from debugging have exact parallels.
- Details When programming, there are often signs that some bug exists like: “the graph my program output is shifted a little bit” = maybe you have an indexing error. In debugging yourself, we often have some impression that something is “not right”. These impressions should be addressed directly and immediately. (Some people have the habit of suppressing worries in favor of excess certainty. That’s not healthy for research.)
- Corner Cases A “corner case” is an input to a program which is extreme in some way. We can often concoct our own corner cases and solve them. If the solution doesn’t match our (mis)understanding, a bug has been found.
- Warnings On The compiler “gcc” has the flag “-Wall” which means “turn all warnings about odd program forms on”. You should always compile with “-Wall” as you immediately realize if you compare the time required to catch a bug that “-Wall” finds with the time required to debug the hard way.
The equivalent for debugging yourself is listening to others carefully. In research, some people have the habit of wanting to solve everything before talking to others. This is usually unhealthy. Talking about the problem that you want to solve is much more likely to lead to either solving it or discovering the problem is uninteresting and moving on.
- Debugging by Design When programming, people often design the process of creating the program so that it is easy to debug. The analogy for us is stepwise mastery—first master your understanding of something basic. Then take the next step, the next, etc…
- Isolation When a bug is discovered, the canonical early trouble shooting step is isolating the bug. For a parse error, what is the smallest program exhibiting the error? For a compiled program: what are the simplest set of inputs which exhibit the bug? For research, what is the simplest example that you don’t understand?
- Representation Change When programming, sometimes a big program simply becomes too unwieldy to debug. In these cases, it is often a good idea to rethink the problem the program is trying to solve. How can you better structure the program to avoid this unwieldiness?
The issue of how to represent the problem is perhaps even more important in research since human brains are not as adept as computers at shifting and using representations. Significant initial thought on how to represent a research problem is helpful. And when it’s not going well,
changing representations can make a problem radically simpler.
Some aspects of debugging a reality misunderstanding don’t have a good analogue for programming because debugging yourself often involves social interactions. One basic principle is that your ego is unhelpful. Everyone (including me) dislikes having others point out when they are wrong so there is a temptation to avoid admitting it (to others, or more harmfully to yourself). This temptation should be actively fought . With respect to others, admitting you are wrong allows a conversation to move on to other things. With respect to yourself, admitting you are wrong allows you to move on to other things. A good environment can help greatly with this problem. There is an immense difference in how people behave under “you lose your job if wrong” and “great, let’s move on”.
What other debugging techniques exist?
As part of a PASCAL project, the Slovenians have been filming various machine learning events and placing them on the web here. This includes, for example, the Chicago 2005 Machine Learning Summer School as well as a number of other summer schools, workshops, and conferences.
There are some significant caveats here—for example, I can’t access it from Linux. Based upon the webserver logs, I expect that is a problem for most people—Computer scientists are particularly nonstandard in their choice of computing platform.
Nevertheless, the core idea here is excellent and details of compatibility can be fixed later. With modern technology toys, there is no fundamental reason why the process of announcing new work at a conference should happen only once and only for the people who could make it to that room in that conference. The problems solved include:
- The multitrack vs. single-track debate. (“Sometimes the single track doesn’t interest me” vs. “When it’s multitrack I miss good talks”
- “I couldn’t attend because I was giving birth/going to a funeral/a wedding”
- “What was that? I wish there was a rewind on reality.”
There are some fears here too. For example, maybe a shift towards recording and placing things on the web will result in lower attendance at a conference. Such a fear is confused in a few ways:
- People go to conferences for many more reasons than just announcing new work. Other goals include doing research, meeting old friends, worrying about job openings, skiing, and visiting new places. There also a subtle benefit of going to a conference: it represents a commitment of time to research. It is this commitment which makes two people from the same place start working together at a conference. Given all these benefits of going to a conference, there is plenty of reason for them to continue to exist.
- It is important to remember that a conference is a process in aid of research. Recording and making available for download the presentations at a conference makes research easier by solving all the problems listed above.
- This is just another new information technology. When the web came out, computer scientists and physicists quickly adopted a “place any paper on your webpage” style even when journals forced them to sign away the rights of the paper to publish. Doing this was simply healthy for the researcher because his papers were more easily readable. The same logic applies to making presentations at a conference available on the web.
Founding a successful new conference is extraordinarily difficult. As a conference founder, you must manage to attract a significant number of good papers—enough to entice the participants into participating next year and to (generally) to grow the conference. For someone choosing to participate in a new conference, there is a very significant decision to make: do you send a paper to some new conference with no guarantee that the conference will work out? Or do you send it to another (possibly less related) conference that you are sure will work?
The conference founding problem is a joint agreement problem with a very significant barrier. Workshops are a way around this problem, and workshops attached to conferences are a particularly effective means for this. A workshop at a conference is sure to have people available to speak and attend and is sure to have a large audience available. Presenting work at a workshop is not generally exclusive: it can also be presented at a conference. For someone considering participation, the only overhead is the direct time and effort involved in participation.
All of the above says that workshops are much easier than conferences, but it does not address a critical question: “Why run a workshop at a conference rather than just a session at the conference?” A session at the conference would have all the above advantages.
There is one more very signficant and direct advantage of a workshop over a special session: workshops are run by people who have a direct and significant interest in their success. The workshop organizers do the hard work of developing a topic, soliciting speakers, and deciding what the program will be. Reputations for the workshop organizer are then built on the success or flop of the workshop. This “direct and signficant interest” aspect of a workshop is the basic reason why franchise systems (think 7-11 or McDonalds) are common and successful.
What does this observation imply about how things could be? For example, we could imagine a conference that is “all workshops”. Instead of having a program committee and program chair, the conference might just have a program chair that accepts or rejects workshop chairs who then organize their own workshop/session. This mode doesn’t seem to exist which is always cautioning, but on the other hand it ‘s not clear this mode has even been tried. NIPS is probably the conference closest to using this approach. For example, a significant number of people attend only the workshops at NIPS.