ISBA 2012 [guest post]
Living in Australia has a few benefits when it comes to ISBA 2012. The most obvious one is that travel to Japan takes less than 24 hours and all occurs within time zones which are fairly close to what I consider “normal time”. While my room mate and other attendees appeared to be in various states of exhaustion and mania (we all deal with a lack of sleep very differently) I spent the Monday morning after registration exploring parts of downtown Kyoto with two other attendees from QUT.
Well rested and ready for action, I managed to stay awake during the foundational topic sessions. I had seen Aad van der Vaart talk about coverage of credible sets this time last year in Veracruz at 8BNP, but having come further with my studies I now understood much more of what was going on and could appreciate the implications on a deeper level. The take-home message “you can be very certain but very wrong”. It’s definitely food for thought as I go ahead with my own work on non-/semi-parametric smoothing.
The standout talks for me so far have been in the Advances in Gaussian Processes, Hierarchies of BNP processes and Beta process sessions. While I don’t work directly in these fields I find them absolutely fascinating and was treated in the GP session to three very good examples of the use of GPs with some very clever intricacies in solving some large scale physical science problems. Cari Kaufman’s presentation, in particular, was a great demonstration of how we can use the properties of GPs and flexible mean estimators to obtain sensible smoothers than interpolate the data we have while giving good estimates of the remaining uncertainty. We had a chat on the way to lunch about the overlap between our work and started thinking about some interesting problems that exist in this overlap.
The Hierarchical NP Bayes session had Emily Fox talking about hierarchies of GPs that take advantage of partitioning and the additive properties of GPs and give us a multiresolution GP modelling technique. Combining a globally smooth GP with smaller scale GPs which can model local and discontinuous behaviour in a straightforward and computationally efficient manner is a really neat way to take care of the multiple scales of behaviour in data. Every time I see what Fox is working on I get really excited about the ways we might be able to use it in my group.
Probably my favourite talk was Tamara Broderick’s talk on the search for exchangeable feature probability functions as a way to characterise latent feature models in the way clustering models have been characterised. I know that Tam spent a lot of time on this talk, both late at night and early in the morning, and it paid off. The moment of beauty, for me, came when she presented an extension to Kingman’s Paintbox that allows for overlapping “partitions” by ensuring that the second feature was shared between the partitions where the first feature was and wasn’t expressed (such that p2|p1 and p2|~p1 are in equal proportions, linking it to the Independence). At that point, the talk stopped being about some interesting models based on the Beta process and became a call to discover what was possible in terms of links between a painting scheme and EFPFs. The paper became available on the arXiv during the Beta Process session
Written at Wednesday morning coffee break.