10 citations · 10 across the 3 of their papers we have counts for
5 papers
Sparse Spectrum Gaussian Process for Bayesian Optimization
Ang Yang, Cheng Li, Santu Rana +2
We propose a novel sparse spectrum approximation of Gaussian process (GP) tailored for Bayesian optimization. Whilst the current sparse spectrum methods provide desired approximati…
Stable Bayesian Optimisation via Direct Stability Quantification
Alistair Shilton, Sunil Gupta, Santu Rana +3
In this paper we consider the problem of finding stable maxima of expensive (to evaluate) functions. We are motivated by the optimisation of physical and industrial processes where…
Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives
Tinu Theckel Joy, Santu Rana, Sunil Gupta +1
In this paper we develop a Bayesian optimization based hyperparameter tuning framework inspired by statistical learning theory for classifiers. We utilize two key facts from PAC le…
Multi-objective Bayesian optimisation with preferences over objectives
Majid Abdolshah, Alistair Shilton, Santu Rana +2
We present a multi-objective Bayesian optimisation algorithm that allows the user to express preference-order constraints on the objectives of the type "objective A is more importa…
A Slice Sampler for Restricted Hierarchical Beta Process with Applications to Shared Subspace Learning
Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh
Hierarchical beta process has found interesting applications in recent years. In this paper we present a modified hierarchical beta process prior with applications to hierarchical…