A Marie Sklodowska-Curie ITN funded by the Horizon2020 program of the European Commission



Adjusting hyper-parameters: First step into Bayesian optimisation of DNNs

by Giles Strong

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”

Science, statistics, and subjectivity

by Giles Strong

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”

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