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a nice review on the wonders of Hierarchical Bayesian models. It cites a paper on probabilistic programming languages that might be relevant given our recent discussions. At Hippo's farewell lunch there was a discussion on how kids are able to learn something as complex as language from a limited amount of observations, while Machine Learning algorithms no matter how many millions of instances you throw at them, don't learn beyond some point. If that subject interested you, you might like this paper.

Had an opportunity to listen to JBT and TLG during one summer school.. if they're half as good in writing as they are in speaking, should be a decent read...

An interesting research centre in California! Focus areas: Business Services Electronic Materials, Devices, & Systems Information & Communication Technologies Biomedical Systems Cleantech

XEROX PARC was definitely heavily involved in computer development: eg. mouse, GUI, ethernet, OO programming, all came out of PARC, and all that without focusing on computers but printers...

aaah its the XEROX centre, didn't know. Yep they made the mouse and then handed it over nicely to Apple after IBM thought it was useless

Keystroke dynamics detection with a Bayesian classifier

Great introduction to the Bayesian view on the workings of the brain, which has been a successful view in explaining many psychological phenomena, visual illusions, etc. One of the possible criticisms on this view is that it neatly separates perception and action.

Determining the "volume" and position of objects inside buildings using wi-fi signal.

another example of bayesian inversion

"The objects on the other side do not even have to move to be detected." Very American way of saying "The objects have to be stationary to be detected"...