53 citations · 85 across the 3 of their papers we have counts for
3 papers
Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces
Kevin Swersky, David Duvenaud, Jasper Snoek +2
In practical Bayesian optimization, we must often search over structures with differing numbers of parameters. For instance, we may wish to search over neural network architectures…
Automated Machine Learning on Big Data using Stochastic Algorithm Tuning
Thomas Nickson, Michael A Osborne, Steven Reece +1
We introduce a means of automating machine learning (ML) for big data tasks, by performing scalable stochastic Bayesian optimisation of ML algorithm parameters and hyper-parameters…
Efficient Bayesian Nonparametric Modelling of Structured Point Processes
Tom Gunter, Chris Lloyd, Michael A. Osborne +1
This paper presents a Bayesian generative model for dependent Cox point processes, alongside an efficient inference scheme which scales as if the point processes were modelled inde…