A few months ago I wrote about some work I was doing on improving the way a certain kind of particle is detected at CMS, by replacing the existing algorithm with a neural network. I recently resumed this work and have now got to the point where I show significant improvement over the existing method. The design of the neural network, however, was one that I imported from some other work, and what I want to do is to adjust it to better suit my problem. Continue reading “Adjusting hyper-parameters: First step into Bayesian optimisation of DNNs”
So, I’m back from my statistics school in Autrans, and Lisbon has managed to get even hotter (currently 31 °C!). Luckily I’m escaping off to Sweden soon, where Google informs me that the weather is much more acceptable – 18 °C. Anyway, I’ve had a bit of time to digest the topics covered during the school, one of which was Bayesian statistics.
I’d had an introduction to Bayesian statistics before at a two-day workshop during my Glasgow masters, and had kind of got the gist of it, but forgotten Continue reading “Science, statistics, and subjectivity”