Sammi The Wonder Penguin!

I didn’t expect to write so much, but it’s supposed to be good documentation, even if overly informal in places and so it continues (from Part 1)…

My Talk/Poster Session

For those who have asked me about this beforehand, you would’ve known that I was rather nervous about this. I’m not a naturally good public speaker and am also afraid of sounding over-rehearsed so it’s tricky divide. I opted (well, more persuaded) for the latter approach, so had lots of preparation; but even so, I was fairly nervous and had a shaky start. It didn’t help that my chair was missing for the first half of my talk as he was double-booked – no panic though, a kind and seemingly experienced member of the audience introduced me and started the session on time (shame I didn’t catch the name, I really should’ve thanked him more).

Anyhow, once I got into the flow, it was grand. Being able to watch it afterwards, although initially very cringe-inducing, is also surprisingly helpful. Once I got over to listening to my very weird accent (no wonder people can’t pin it!), I tried to objectively evaluate it and figure out what needs work. I think I need to be more aware of utterances (i.e. um um UM), even if it’s impossible to control exactly, better pacing might be a semi-solution. I’m glad I gestured (but not overly à la wavy arms) as I think it helps alleviate dullness. I was also more monotonic than I’d realised, which is another thing I think could be worked on. Overall I’m reasonably happy with how it went. I was able to answer the questions at the end (naturally, I could’ve answered better in retrospect, but I think it was really the best I could’ve done at the time). My only regret was not being able to catch the second person who asked a question to continue the conversation ‘offline’ :/

As to the poster session – essentially didn’t happen I had brought the poster back to my hotel room on Monday having had a colleague help transport it over. Friday morning came and I realised it’s gone. I had searched my room thoroughly and my conclusion was it was thrown out by the cleaners. Given that it was in a cardboard tube which I had very haphazardly chopped off bits of to get it to fit, it was reasonable to mistake for rubbish. This was very frustrating at the time but in retrospect, even if I had realised it was missing earlier, it still might not have been recovered. Moreover, I decided to go to some talks arranged for Industry Day during my alloted time so my time was spent reasonably productively either way.

Other/Overall impressions

I don’t think I can spend much more time on expanding any more thoughts but here’s some final snippets:

• I’ve been out of out of touch with the AI community in a while (~3 years) so it was interesting to see what’s going on in (sub)field(s).
• There is a project, AISN, which is attempting to create a sort of AI online community based on the conference attendees. I do hope it takes off, it’s an interesting idea and data is always good…
• I am not sure I liked the multiple-track format, but I guess that’s unavoidable with such a broad conference. And for the same reason, it was a bit difficult to find people who worked in the same field, but I suppose the workshops were organised for this – slightly more specialist.
• The schedule was also quite tight and packed which meant stress at times – and tiring!
• However, I did quite enjoyed those extra events – the delightfully geeky Casparo opera at the beautiful Palau de la Música Catalana, not-so-yummy “banquet” at Poble Espanyol, and I think the aforementioned Industry day talks were useful, even if a bit commercial.

Summary/What I’ve learned

• Large conference, broad areas -> plan what to do in advance.
• Look at organising committee of workshops to see if worth/has future. Take advantage of tutorials.
• Best quality talks are usually invited ones. Especially seasoned researchers who aren’t just there to advertise their methods, but their field.
• Don’t be afraid to ask questions. I should apply this more myself.
• Networking isn’t as difficult as I expected. People are open, but do realise they also have personal agendas which may or may not align with yours.
• Although may sound anti-previous point, don’t be afraid to make new friends – people have more sides than just their academic ones

Honorable Mention: ICWSM

IJCAI was co-located (in that both were in Barcelona) with ICWSM this year and a few colleagues of mine attended it. Though I was not officially supposed to, I attended one talk there by Jimmy Lin entitled “Twitter and Data Science” who is an academic but taking a couple of sabbatical years to work at Twitter. His talk mentions (see below) what types of techniques are often applied to Twitter data which reminded me of the concept of “builders and studiers” we’d used at the Web Science Summer School.

At this point, I must also extend a big congrats to John Breslin who I believe to have had a major part in the result that ICWSM will be held in Dublin next year!

Last words (not terribly important)

And finally, the rumours have been quashed and though we knew IJCAI was to be held in Beijing in 2013, people lobbying for Melbourne in 2015, despite their t-shirts have been declined – and will be held in Argentina (Buenos Aires, I think). Moreover, it has been confirmed that it will become an annual conference post-2015:

Who knows how the community will evolve by then, and whether I’ll have the chance to attend again. I would love to, but given the scope of it, I’d see it more as a high-end educational holiday than a directly relevant work week (especially given the exotic locations ). I was certainly inspired by it, and feel the need to push a bit more – my reading list will never end!

I was at IJCAI last week; this was my first major academic conference and I very much enjoyed it.

IJCAI is a well-established bi-annual conference (since 1969) and the acronym stands for “International Joint Conference(s) on Artificial Intelligence”. The term “Artificial Intelligence” is an interesting one, and it came up in several conversations throughout, though I won’t go into it here (we can pub-talk this if we meet!). But in short, it spawned from the fact that it is a very large and broad conference with ~1500 participants, and I think a few of us were struggling to figure out where we fit.

Tangential Modularity Rant

Personally, I was playing the community-finding card, specifically a community of roles in the network (at least that’s what I’ve been convincing myself!), so I was browsing the clustering, web mining topics, and bits of the search landscape. My impression is that there is a lot of work going on that focussed on recommendation/prediction (I suppose this is a kind of ‘intelligence’ after all, so shouldn’t be surprising) but I also noticed that Newman’s modularity heuristic was very popular.  It was often used as a basis of a sub-part of a solution (to another problem) or formulated differently in order to scale it up, with little requirement in interpretation of results, which I think is a pity.

In other words, results sections often consisted of graphs showing how fast so and so performed in comparison to other methods, but the found clusters themselves usually omitted. This is fair enough if they were generated from synthetic data, but for any real-world data, the only argument as to how they are good is that the smaller the Q value, the better it is which is too weak IMHO. If I agree with your assumptions, then perhaps this makes sense, but it does require a leap of faith, and Fortunato & Barthélemy does a good job of making this leap look bigger than a simple hop.

Furthermore, although it was highlighted to me that my approach may be too specific to social networks (semi-supervised approach to finding roles), that for very large networks it may not be possible to interpret everything, I still think there should be a place for thoughts on the trees than the wood. In particular, the very first workshop talk I attended, Detecting Communities from Social Tagging Networks Based on Tripartite Modularity (as well as a few others in the IJCAI proceedings itself), at least tried to show some of the clustered results and acknowledged that methods beyond modularity may be considered. Ok, less rant, more conference details.

Workshops/Tutorials

The conference officially started on Monday evening but workshops and tutorials were run during the weekend (and including the Monday) before. I took part in the Link Analysis in Heterogeneous Information Networks workshop which I unfortunately have to say, wasn’t very well-organised. The talks were interesting enough, but it became clear that not a lot of thought was put into the scheduling of them; there wasn’t really any themes within/connecting the sessions.

The timing was also a bit off. Workshops were held in parallel with specific times for breaks, and we didn’t align to them in the second half of the day which resulted in some confusion and the workshop finishing early. There was also promise of a wiki where the slides and information on participants were to be put up, which I thought was a good idea at the time but I haven’t heard anything about it yet… However, all workshop proceedings are available in one place, which is handy. As for recommendations, I would look at the Web Mining one in the tutorials.

Invited Talks

I didn’t manage to make it to all of them (9am Barcelona time meant 8am Irish time, which, combined with 20-30 minute journey is a near-impossible feat for me). However, of the ones I did attend, two particularly stuck out – Daphne Koller who spoke about “Rich probabilistic models for image understanding” and Jonathon Schaeffer on “The Games People Play Revisited”. This is not to say the other talks weren’t well presented but these two (I felt) struck the right balance between detail and, what I consider often difficult to do without sounding like a blind fan, genuine enthusiasm & passion.

Remember, although they were addressing to a very broad audience, a common theme is that they all have a fairly technical and critical minds, which can be hard to please. Both formats of the talks were similar in that they stated the problem in plain English terms, and then showed the incremental (but important) developments in the field – how aspects of one approach worked, why it didn’t overall, what approach was popular, what inspired a new one, and what they think is the “future”. I especially like Jonathon’s slide below (quoting his wife), which he very proudly gave his response to each line, and in particular to the final one where he said he didn’t know what that meant – this (I assume he meant research into games) is his life

Note I’ve ended up splitting this entry into two parts, as I had more to say than I’d expected (here’s Part 2).