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High-dimensional black-box optimisation remains an important yet notoriously challenging problem.
Axiomatisations of the average and a further generalisation of monotonic sequences
John Bibby · 1974
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Efficient global optimization of expensive black-box functions
Donald R Jones, Matthias Schonlau, and William J Welch · 1998
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The mnist database of handwritten digits
Yann LeCun · 1998
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Jacques Hadamard: A Universal Mathematician
Vladimir Mazya and Tatyana Shaposhnikova · 1999
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A review of trust region algorithms for optimization
Ya-xiang Yuan · 2000
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Random forests
Leo Breiman · 2001
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Complexity classifications of boolean constraint satisfaction problems
Nadia Creignou, Sanjeev Khanna, and Madhu Sudan · 2001
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Diffusion kernels on graphs and other discrete input spaces
Risi Kondor and John D. Lafferty · 2002
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Gaussian processes for machine learning
Carl Edward Rasmussen · 2006
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Eric Brochu, Vlad M Cora, and Nando De Freitas · 2010
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Kriging is well-suited to parallelize optimization
David Ginsbourger, Rodolphe Le Riche, and Laurent Carraro · 2010
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Contamination control in food supply chain
Yingjie Hu, JianQiang Hu, Yifan Xu, Fengchun Wang, and Rong Zeng Cao · 2010
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Gaussian process optimization in the bandit setting: No regret and experimental design
Niranjan Srinivas, Andreas Krause, Sham Kakade, and Matthias Seeger · 2010
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Algorithms for hyper-parameter optimization
James Bergstra, Rémi Bardenet, Yoshua Bengio, and Balázs Kégl · 2011
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Sequential model-based optimization for general algorithm configuration
Frank Hutter, Holger H Hoos, and Kevin Leyton-Brown · 2011
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Contextual Gaussian process bandit optimization
Andreas Krause and Cheng S Ong · 2011
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Restart strategies in optimization: parallel and serial cases
Oleg V Shylo, Timothy Middelkoop, and Panos M Pardalos · 2011
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Practical Bayesian optimization of machine learning algorithms
Jasper Snoek, Hugo Larochelle, and Ryan P Adams · 2012
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Bayesian optimization in high dimensions via random embeddings
Ziyu Wang, Masrour Zoghi, Frank Hutter, David Matheson, N Freitas, et al · 2013
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A warped kernel improving robustness in Bayesian optimization via random embeddings
Mickaël Binois, David Ginsbourger, and Olivier Roustant · 2015
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High dimensional Bayesian optimisation and bandits via additive models
Kirthevasan Kandasamy, Jeff Schneider, and Barnabás Póczos · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Xgboost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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GPyOpt: A Bayesian optimization framework in python
GPyOpt · 2016
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Taking the human out of the loop: A review of Bayesian optimization
Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P Adams, and Nando de Freitas · 2016
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Bayesian optimization in a billion dimensions via random embeddings
Ziyu Wang, Frank Hutter, Masrour Zoghi, David Matheson, and Nando de Feitas · 2016
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Mixed-variable Bayesian optimization
Erik Daxberger, Anastasia Makarova, Matteo Turchetta, and Andreas Krause · 2019
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Scalable global optimization via local Bayesian optimization
David Eriksson, Michael Pearce, Jacob Gardner, Ryan D Turner, and Matthias Poloczek · 2019
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Efficient high dimensional Bayesian optimization with additivity and quadrature fourier features
Mojmír Mutnỳ and Andreas Krause · 2019
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A framework for Bayesian optimization in embedded subspaces
Amin Nayebi, Alexander Munteanu, and Matthias Poloczek · 2019
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Combinatorial Bayesian optimization using the graph cartesian product
Changyong Oh, Jakub Tomczak, Efstratios Gavves, and Max Welling · 2019
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Parallel and distributed Thompson sampling for large-scale accelerated exploration of chemical space
José Miguel Hernández-Lobato, James Requeima, Edward O Pyzer-Knapp, and Alán Aspuru-Guzik · 2017
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High dimensional Bayesian optimization with elastic gaussian process
Santu Rana, Cheng Li, Sunil Gupta, Vu Nguyen, and Svetha Venkatesh · 2017
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Batched high-dimensional Bayesian optimization via structural kernel learning
Zi Wang, Chengtao Li, Stefanie Jegelka, and Pushmeet Kohli · 2017
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Bayesian optimization of combinatorial structures
Ricardo Baptista and Matthias Poloczek · 2018
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A tutorial on Bayesian optimization
Peter I Frazier · 2018
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Gpytorch: Blackbox matrix-matrix gaussian process inference with gpu acceleration
Jacob R Gardner, Geoff Pleiss, David Bindel, Kilian Q Weinberger, and Andrew Gordon Wilson · 2018
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Autozoom: Autoencoder-based zeroth order optimization method for attacking black-box neural networks
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On the choice of the low-dimensional domain for global optimization via random embeddings
Mickaël Binois, David Ginsbourger, and Olivier Roustant · 2020
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Black-box mixed-variable optimisation using a surrogate model that satisfies integer constraints
Laurens Bliek, Sicco Verwer, and Mathijs de Weerdt · 2020
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Sparse-rs: a versatile framework for query-efficient sparse black-box adversarial attacks
Francesco Croce, Maksym Andriushchenko, Naman D Singh, Nicolas Flammarion, and Matthias Hein · 2020
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Combinatorial black-box optimization with expert advice
Hamid Dadkhahi, Karthikeyan Shanmugam, Jesus Rios, Payel Das, Samuel C Hoffman, Troy David Loeffler, and Subramanian Sankaranarayanan · 2020
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Optimizing discrete spaces via expensive evaluations: A learning to search framework
Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, and Alan Fern · 2020
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Dealing with categorical and integer-valued variables in Bayesian optimization with Gaussian processes
Eduardo C Garrido-Merchán and Daniel Hernández-Lobato · 2020
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Re-examining linear embeddings for high-dimensional bayesian optimization
Ben Letham, Roberto Calandra, Akshara Rai, and Eytan Bakshy · 2020
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Bayesian optimization for categorical and category-specific continuous inputs
Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, and Svetha Venkatesh · 2020
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Provably efficient online hyperparameter optimization with population-based bandits
Jack Parker-Holder, Vu Nguyen, and Stephen J Roberts · 2020
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Amortized bayesian optimization over discrete spaces
Kevin Swersky, Yulia Rubanova, David Dohan, and Kevin Murphy · 2020
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Fourier representations for black-box optimization over categorical variables
Hamid Dadkhahi, Jesus Rios, Karthikeyan Shanmugam, and Payel Das · 2021
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