1 citations · 1 across the 2 of their papers we have counts for
3 papers
Accelerating Multi-Objective Bayesian Optimisation via Predictive-Gradient Catalysts
Alma Rahat, Tinkle Chugh, Jonathan Fieldsend +1
This paper presents a general acceleration mechanism for multi-objective Bayesian optimisation (MOBO) that leverages Gaussian process predictive gradients as auxiliary signals. Rat…
Efficient Approximation of Expected Hypervolume Improvement using Gauss-Hermite Quadrature
Alma Rahat, Tinkle Chugh, Jonathan Fieldsend +2
Many methods for performing multi-objective optimisation of computationally expensive problems have been proposed recently. Typically, a probabilistic surrogate for each objective…
What Makes an Effective Scalarising Function for Multi-Objective Bayesian Optimisation?
Clym Stock-Williams, Tinkle Chugh, Alma Rahat +1
Performing multi-objective Bayesian optimisation by scalarising the objectives avoids the computation of expensive multi-dimensional integral-based acquisition functions, instead o…