Peekaboo

John Langford published a great article on his blog today: http://hunch.net/?p=1822 Don't miss out on it ;)

While reading around MetaOptimize , I found a reference to the book " Bayesian Reasoning and Machine Learning" by David Barber. You can download the pdf for free and it will be published soon in Cambridge University Press. It comes with many Matlab examples and seems worth taking a look at :)

Ok this is probably my last post about NIPS 2010. First of all, I became a big fan of Zoubin Ghahramani . He is a great speaker and quite funny. There are quite some video lecture by him that are linked on his personal page: here and here . They are mostly about graphical models and nonparametric methods. He had an invited talk at the transfer learning workshop about cascading indian buffet process where he illustrated the idea behind this method: "Every dish is a customer in another restaurant. Somebody pointed out that this is kind of canabilistic. We didn't realize that the IBP analogy goes really deep.... dark ... and wrong." This work is about learning the structure of directed graphical models using IBP priors on the graph structure ( pdf ). When asked about three way interaction, which this model does not feature - in contrast to many deep graphical models studied at the moment - he argued that latent variables induce covariances by marginalization on the lay...

Apparently, they can! Using just a naive Bayesian classifier and simple features, it is possible to play chess. Who would have thought?