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Bayesian optimisation (BO) algorithms have shown remarkable success in applications involving expensive black-box functions.
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D. R. Jones, M. Schonlau, and W. J. Welch · 1998
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Lior Rokach · 2010
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Javad Azimi, Alan Fern, and Xiaoli Z. Fern · 2010
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Regret bounds for Gaussian process bandit problems
Steffen Grünewälder, Jean Yves Audibert, Manfred Opper, and John Shawe-Taylor · 2010
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Convergence Rates of Efficient Global Optimization Algorithms
Adam D. Bull · 2011
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Frank Hutter, Holger H Hoos, and Kevin Leyton-Brown · 2011
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James S Bergstra, Rémi Bardenet, Yoshua Bengio, and Balázs Kégl · 2011
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Franz Graf, Hans-Peter Kriegel, Matthias Schubert, Sebastian Pölsterl, and Alexander Cavallaro · 2011
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Jasper Snoek, Hugo Larochelle, and Ryan P. Adams · 2012
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Masashi Sugiyama, Hirotaka Hachiya, Makoto Yamada, Jaak Simm, and Hyunha Nam · 2012
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Yasin Abbasi-Yadkori · 2012
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The mnist database of handwritten digit images for machine learning research
Li Deng · 2012
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Stéphane Boucheron, Gábor Lugosi, and Pascal Massart · 2013
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Gianluca Detommaso, Tiangang Cui, Alessio Spantini, Youssef Marzouk, and Robert Scheichl · 2018
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Parallelised Bayesian optimisation via Thompson sampling
Kirthevasan Kandasamy, Akshay Krishnamurthy, Jeff Schneider, and Barnabas Poczos · 2018
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Neural tangent kernel: Convergence and generalization in neural networks
Arthur Jacot, Franck Gabriel, and Clément Hongler · 2018
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Gaussian Process Behaviour in Wide Deep Neural Networks
Alexander G. de G. Matthews, Jiri Hron, Mark Rowland, Richard E. Turner, and Zoubin Ghahramani · 2018
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Johnathan M Bardsley, Antti Solonen, Heikki Haario, and Marko Laine · 2014
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Scalable Bayesian optimization using deep neural networks
Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, M Patwary, Prabhat, and R Adams · 2015
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Matej Balog and Yee Whye Teh · 2015
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Adam: A Method for Stochastic Optimization
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Jost Tobias Springenberg, Klein Aaron, Stefan Falkner, and Frank Hutter · 2016
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Rafael Oliveira, Lionel Ott, and Fabio Ramos · 2019
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PyTorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Bayesian Optimization by Density-Ratio Estimation
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On information gain and regret bounds in gaussian process bandits
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An efficient batch-constrained Bayesian optimization approach for analog circuit synthesis via multiobjective acquisition ensemble
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MBORE: Multi-objective Bayesian optimisation by density-ratio estimation
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