I’m working on a paper together with a PhD student who is technically in my lab, but geographically in Cuba. For some reason, neither SVN nor Dropbox were working, and I was afraid we would have to resort to emailing the paper to each other (the horror!). Then during lunch I thought that we could just use GoogleDocs for the LateX file, or maybe that GoogleDocs even supported LateX. It’s such a simple idea somebody had to already have thought about this!
And indeed, ShareLateX has! You can sign up and create LateX projects and invite others to collaborate with you. Then you have your main file, any other files you want to add, and a button that compiles the .tex file into .pdf (and you can even choose whether you want the latex or pdftex version).
Again, the idea might seem very simple, but I’m still somewhat in awe… You can work on the same LateX file real-time, without waiting for somebody to save, commit or upload a new version. This is very motivating because you see the paper changing so quickly. It is also much easier to decide things together, such as adding that new section, because you already see how it would change the paper. Last but not least, you are all using the same compiler, so you can’t mess up the tex file for each other 🙂
There is a down side, of course. The free version only supports 2 collaborators and there is no version control. As soon as you want an upgrade, you get the “Collaborator” account which allows 10 collaborators per project but also costs you $15 a month. Not a lot if the only thing you do is write papers with people overseas, but too much if that only happens once or twice a year. I only hope that universities realize how service is great for the researchers’ productivity, and offer it to employees free of charge 🙂
This post originally appeared on my previous blog.
After my one-year evaluation, the first thing I did was sign up for a course on presentation skills. To be honest, I hesitated a bit at first, but I started hearing quite a few good things about Art of Presenting Science, so I decided to see for myself what that was all about. I really, really loved it! I can’t really summarize my experiences in a few sentences, so perhaps I will dedicate a whole post to this. I tried to put a few of the things I learned to the test when presenting my work at the meeting of the NVPHBV (Dutch Society for Pattern Recognition and Image Processing), and at the Benelearn conference in Gent, Belgium.
As for research, I was pursuing several directions that are relevant to Multiple Instance Learning, learning with dissimilarities, or both. A few of these ideas resulted in submissions to conferences, while others were abandoned after a while. Perhaps “abandoned” is not the correct word to describe the situation, and “on the shelf” would be better. The ideas are still very interesting, but at the time I did not have enough insight to turn them into something that could be published. I hope that I will have more luck with this in 2013 🙂
In the summer it was time to take a break from my own research, and learn a lot about what others are doing at the Machine Learning Summer School in Santa Cruz, California in the US. The summer school consisted of two weeks of lectures from people from academia and from industry. The proximity to Silicon Valley ensured a lot of interesting talks by Google, Facebook and other companies that have a lot of data and therefore do a lot of machine learning. Next to all the talks, it was a great experience to meet other researchers from all of the world and compare notes on everything from doing a PhD to making tacos. I hope we will meet again!
As if that wasn’t enough traveling, I received the decisions on two papers that were submitted a few months ago. Both were accepted as poster presentations: “Does one rotten apple spoil the whole barrel” at the International Conference on Pattern Recognition (ICPR), and “Class-Dependent Bag Dissimilarities for Multiple Instance Learning” at the Structural, Syntactic and Statistical Pattern Recognition (S+SSPR) workshop. S+SSPR was held in Hiroshima, and ICPR was held in Tsukuba, close to Tokyo. With an extra day to recover from jetlag and a few days (because three weeks in the US aren’t cheap) for sightseeing, this meant a two-week trip to Japan. One of my posters in action:
I enjoyed both conferences although they were completely different from each other. S+SSPR was very small, which allowed informal discussions more often and attending a lot of the talks. I also noticed the same type of close community (but with a different subset of researchers) that I saw at Multiple Classifier Systems a year earlier. ICPR was very big, which was a new experience for me. The program booklet was as large as the proceedings of some conferences! Therefore it was quite difficult to choose which talks to attend. I found out that often, my first impression (such as “this is relevant to my research” or “I won’t understand this at all”) was wrong. In fact, I was pleasantly surprised by a few talks about unrelated topics, but given by a great presenter. There is still a lot to learn for me there.
Although I thought I could deal with time differences pretty well, I did have a few sleepless nights in Japan. On one of these nights, I had an idea about the relationship of my own work to a quite successful MIL classifier. Who wouldn’t get inspired if you are surrounded by wonderful things like this:
Instead of scribbling the idea down with a few words, arrows etc, which is what I usually do, I actually started writing the paper. I didn’t get very far while I was in Japan, but I did discuss the idea and let it develop. After the decision to made to submit a paper to Multiple Classifier Systems 2013 (I admit, I loved MCS 2011 so much I just couldn’t resist), the whole process of writing and submitting the paper cost me about a month. Perhaps that might be long for some people, but for me it was definitely a record. I’m also very happy with the process, so perhaps I will try this more often (starting to write a paper as soon as the idea is there).
After going on vacation and celebrating the start of 2011, my first official working day was on the 3rd of January 2011. Now my job was to work on a different pattern recognition topic: Dissimilarity-based Multiple Instance Learning.
However, for a while I still continued working on my MSc subject in order to write a paper for Multiple Classifier Systems 2011. The paper “Pruned Random Subspace Method for One-Class Classifiers” (as you can guess, the regular method was not good enough) was accepted for presentation!
In June we went to Naples, Italy for the MCS 2011 conference. Here is an impression of me presenting:
Here is an impression of the conference lunch:
Besides the great food, wine and weather I really really enjoyed the conference. I finally got to meet the people behind all the papers I have been citing and I got a feel for the type of community that all these people formed. After the conference, we had a few days to see more of Naples, the Vesuvius volcano and the ruins of Pompei.
As my next project, I helped with a journal paper that a colleague of mine was writing, “Bridging Feature and Structure Representations in Graph Matching”. Without getting into too many details, we wanted to classify objects that are represented as attributed graphs, while varying the importance of the attributes (features) or the actual graph structure. We investigated two ways to do this: using a graph edit distance and using graph kernels, which was my part. Besides learning a lot about graph kernels, I really enjoyed this project because of the regular meetings and discussions and my responsibility to the other people involved.
In September, it was time to go to Italy again, now for the Similarity-based Pattern Recognition Workshop (SIMBAD) 2011 in Venice. My supervisor presented the paper “Bag Dissimilarities for Multiple Instance Learning”, which is also what most of my current work is about. Unfortunately, I was very ill during the conference, so I didn’t have such a good conference and sightseeing experience as in Naples.
Next to research, some of my time was spent on education. I followed courses on topics related to image processing and bioinformatics, and also did the online Machine Learning course, which was very helpful. I also got to experience education from a different side a little bit while assisting in Pattern Recognition courses for PhD students and for people from industry.
In the end of the year, I had my go/no-go presentation and I received a go, together with a lot of helpful advice on how to improve my work. The main points were to become more comfortable with mathematics, be more precise in why I’m pursuing a certain direction in research, and to improve my presentation skills.