43 citations · 63 across the 9 of their papers we have counts for
9 papers
Bayesian Optimization for Building Social-Influence-Free Consensus
Masaki Adachi, Siu Lun Chau, Wenjie Xu +3
We introduce Social Bayesian Optimization (SBO), a vote-efficient algorithm for consensus-building in collective decision-making. In contrast to single-agent scenarios, collective…
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal
Juliusz Ziomek, Masaki Adachi, Michael A. Osborne
Bayesian Optimization (BO) is widely used for optimising black-box functions but requires us to specify the length scale hyperparameter, which defines the smoothness of the functio…
Principled Bayesian Optimisation in Collaboration with Human Experts
Wenjie Xu, Masaki Adachi, Colin N. Jones +1
Bayesian optimisation for real-world problems is often performed interactively with human experts, and integrating their domain knowledge is key to accelerate the optimisation proc…
Time-Varying Gaussian Process Bandits with Unknown Prior
Juliusz Ziomek, Masaki Adachi, Michael A. Osborne
Bayesian optimisation requires fitting a Gaussian process model, which in turn requires specifying prior on the unknown black-box function -- most of the theoretical literature ass…
Looping in the Human Collaborative and Explainable Bayesian Optimization
Masaki Adachi, Brady Planden, David A. Howey +5
Like many optimizers, Bayesian optimization often falls short of gaining user trust due to opacity. While attempts have been made to develop human-centric optimizers, they typicall…
Adaptive Batch Sizes for Active Learning A Probabilistic Numerics Approach
Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen +4
Active learning parallelization is widely used, but typically relies on fixing the batch size throughout experimentation. This fixed approach is inefficient because of a dynamic tr…
Machine Learning Benchmarks for the Classification of Equivalent Circuit Models from Electrochemical Impedance Spectra
Joachim Schaeffer, Paul Gasper, Esteban Garcia-Tamayo +10
Analysis of Electrochemical Impedance Spectroscopy (EIS) data for electrochemical systems often consists of defining an Equivalent Circuit Model (ECM) using expert knowledge and th…
Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian Quadrature
Masaki Adachi, Yannick Kuhn, Birger Horstmann +3
A wide variety of battery models are available, and it is not always obvious which model `best' describes a dataset. This paper presents a Bayesian model selection approach using B…
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination
Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen +2
Calculation of Bayesian posteriors and model evidences typically requires numerical integration. Bayesian quadrature (BQ), a surrogate-model-based approach to numerical integration…