Timezone: »
Traditional methods for kernel selection rely on parametric kernel functions or a combination thereof and although the kernel hyperparameters are tuned, these methods often provide sub-optimal results due to the limitations induced by the parametric forms. In this paper, we propose a novel formulation for kernel selection using efficient Bayesian optimisation to find the best fitting non-parametric kernel. The kernel is expressed using a linear combination of functions sampled from a prior Gaussian Process (GP) defined by a hyperkernel. We also provide a mechanism to ensure the positive definiteness of the Gram matrix constructed using the resultant kernels. Our experimental results on GP regression and Support Vector Machine (SVM) classification tasks involving both synthetic functions and several real-world datasets show the superiority of our approach over the state-of-the-art.
Author Information
Arun Kumar Anjanapura Venkatesh (Deakin University)
Alistair Shilton (Deakin University)
Santu Rana (Deakin University)
Sunil Gupta (Deakin University)
Svetha Venkatesh (Deakin University)
More from the Same Authors
-
2021 : Offline neural contextual bandits: Pessimism, Optimization and Generalization »
Thanh Nguyen-Tang · Sunil Gupta · A. Tuan Nguyen · Svetha Venkatesh -
2021 Poster: Model-Based Episodic Memory Induces Dynamic Hybrid Controls »
Hung Le · Thommen Karimpanal George · Majid Abdolshah · Truyen Tran · Svetha Venkatesh -
2020 Poster: Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces »
Hung Tran-The · Sunil Gupta · Santu Rana · Huong Ha · Svetha Venkatesh -
2019 Poster: Bayesian Optimization with Unknown Search Space »
Huong Ha · Santu Rana · Sunil Gupta · Thanh Nguyen-Tang · Hung Tran-The · Svetha Venkatesh -
2019 Poster: Multi-objective Bayesian optimisation with preferences over objectives »
Majid Abdolshah · Alistair Shilton · Santu Rana · Sunil Gupta · Svetha Venkatesh -
2018 Poster: Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation »
Shivapratap Gopakumar · Sunil Gupta · Santu Rana · Vu Nguyen · Svetha Venkatesh -
2018 Poster: Variational Memory Encoder-Decoder »
Hung Le · Truyen Tran · Thin Nguyen · Svetha Venkatesh -
2017 Poster: Process-constrained batch Bayesian optimisation »
Pratibha Vellanki · Santu Rana · Sunil Gupta · David Rubin · Alessandra Sutti · Thomas Dorin · Murray Height · Paul Sanders · Svetha Venkatesh -
2017 Spotlight: Process-constrained batch Bayesian optimisation »
Pratibha Vellanki · Santu Rana · Sunil Gupta · David Rubin · Alessandra Sutti · Thomas Dorin · Murray Height · Paul Sanders · Svetha Venkatesh