21 citations · 40 across the 2 of their papers we have counts for
3 papers
stat.ML2019★ 21 cited
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning
Diego Granziol, Binxin Ru, Stefan Zohren +3
Efficient approximation lies at the heart of large-scale machine learning problems. In this paper, we propose a novel, robust maximum entropy algorithm, which is capable of dealing…
stat.ML2019
Bayesian Optimisation over Multiple Continuous and Categorical Inputs
Binxin Ru, Ahsan S. Alvi, Vu Nguyen +2
Efficient optimisation of black-box problems that comprise both continuous and categorical inputs is important, yet poses significant challenges. We propose a new approach, Continu…
stat.ML2019★ 19 cited
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation
Ahsan S. Alvi, Binxin Ru, Jan Calliess +2
Batch Bayesian optimisation (BO) has been successfully applied to hyperparameter tuning using parallel computing, but it is wasteful of resources: workers that complete jobs ahead…