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Bayesian optimization has recently emerged as a popular method for the sample-efficient optimization of expensive black-box functions.
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A stochastic radial basis function method for the global optimization of expensive functions
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Fast computation of the multi-points expected improvement with applications in batch selection
C. Chevalier and D. Ginsbourger · 2013
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Combining radial basis function surrogates and dynamic coordinate search in high-dimensional expensive black-box optimization
R. G. Regis and C. A. Shoemaker · 2013
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Heteroscedastic treed Bayesian optimisation
J.-A. M. Assael, Z. Wang, B. Shahriari, and N. de Freitas · 2014
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Active learning of linear embeddings for Gaussian processes
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The nlopt nonlinear-optimization package, 2014
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E. Jones, T. Oliphant, and P. Peterson · 2014
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Input warping for Bayesian optimization of non-stationary functions
J. Snoek, K. Swersky, R. Zemel, and R. Adams · 2014
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A warped kernel improving robustness in Bayesian optimization via random embeddings
M. Binois, D. Ginsbourger, and O. Roustant · 2015
Practical Bayesian optimization for model fitting with Bayesian adaptive direct search
L. Acerbi and W. Ji · 2017
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Local Bayesian optimization of motor skills
R. Akrour, D. Sorokin, J. Peters, and G. Neumann · 2017
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Discovering and exploiting additive structure for Bayesian optimization
J. Gardner, C. Guo, K. Weinberger, R. Garnett, and R. Grosse · 2017
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Parallel and distributed Thompson sampling for large-scale accelerated exploration of chemical space
J. M. Hernández-Lobato, J. Requeima, E. O. Pyzer-Knapp, and A. Aspuru-Guzik · 2017
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Bayesian optimization with gradients
J. Wu, M. Poloczek, A. G. Wilson, and P. Frazier · 2017
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Bayesian optimization of combinatorial structures
R. Baptista and M. Poloczek · 2018
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Active subspaces: Emerging ideas for dimension reduction in parameter studies , volume 2
P. G. Constantine · 2015
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High dimensional Bayesian optimisation and bandits via additive models
K. Kandasamy, J. Schneider, and B. Póczos · 2015
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Global optimization with sparse and local Gaussian process models
T. Krityakierne and D. Ginsbourger · 2015
Cited alongside, same era.
Differentiating the multipoint expected improvement for optimal batch design
S. Marmin, C. Chevalier, and D. Ginsbourger · 2015
Cited alongside, same era.
Parallel predictive entropy search for batch global optimization of expensive objective functions
A. Shah and Z. Ghahramani · 2015
Cited alongside, same era.
Scalable Bayesian optimization using deep neural networks
J. Snoek, O. Rippel, K. Swersky, R. Kiros, N. Satish, N. Sundaram, M. Patwary, M. Prabhat, and R. Adams · 2015
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Scaling Gaussian process regression with derivatives
D. Eriksson, K. Dong, E. Lee, D. Bindel, and A. G. Wilson · 2018
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A tutorial on Bayesian optimization
P. I. Frazier · 2018
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GPyTorch: Blackbox matrix-matrix Gaussian process inference with GPU acceleration
J. Gardner, G. Pleiss, K. Q. Weinberger, D. Bindel, and A. G. Wilson · 2018
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Parallelised Bayesian optimisation via Thompson sampling
K. Kandasamy, A. Krishnamurthy, J. Schneider, and B. Póczos · 2018
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Optimization, fast and slow: Optimally switching between local and Bayesian optimization
M. McLeod, S. Roberts, and M. A. Osborne · 2018
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Efficient high dimensional Bayesian optimization with additivity and quadrature Fourier features
M. Mutny and A. Krause · 2018
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BOCK : Bayesian optimization with cylindrical kernels
C. Oh, E. Gavves, and M. Welling · 2018
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High-dimensional Bayesian optimization via additive models with overlapping groups
P. Rolland, J. Scarlett, I. Bogunovic, and V. Cevher · 2018
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A tutorial on Thompson sampling
D. J. Russo, B. Van Roy, A. Kazerouni, I. Osband, Z. Wen, et al · 2018
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Batched large-scale Bayesian optimization in high-dimensional spaces
Z. Wang, C. Gehring, P. Kohli, and S. Jegelka · 2018
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On the choice of the low-dimensional domain for global optimization via random embeddings
M. Binois, D. Ginsbourger, and O. Roustant · 2019
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A framework for bayesian optimization in embedded subspaces
A. Nayebi, A. Munteanu, and M. Poloczek · 2019
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