Improving Adaptive Bayesian Optimization with Spectral Mixture Kernel

Author:

Raj Harsh,Dey Suvodip,Gupta Hiransh,Srijith P. K.

Publisher

Springer International Publishing

Reference8 articles.

1. Nyikosa, F.M., Osborne, M.A., Roberts, S.J.: Bayesian optimization for dynamic problems. arXiv preprint arXiv:1803.03432 (2018)

2. Nyikosa, F.M.: Adaptive Bayesian optimization for dynamic problems. Ph.D. thesis, University of Oxford (2018)

3. Shahriari, B., Swersky, K., Wang, Z., Adams, R.P., De Freitas, N.: Taking the human out of the loop: a review of bayesian optimization. Proc. IEEE 104(1), 148–175 (2015)

4. Wilson, A., Adams, R.: Gaussian process kernels for pattern discovery and extrapolation. In: International Conference on Machine Learning, pp. 1067–1075 (2013)

5. Srinivas, N., Krause, A., Kakade, S.M., Seeger, M.W.: Information-theoretic regret bounds for gaussian process optimization in the bandit setting. IEEE Trans. Inf. Theory 58(5), 3250–3265 (2012)

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