Fetching the paper…
Reading the bibliography…
Bayesian Optimisation (BO) refers to a suite of techniques for global optimisation of expensive black box functions, which use introspective Bayesian models of the function to efficiently search for the optimum.
On the Likelihood that one Unknown Probability Exceeds Another in View of the Evidence of Two Samples
William R Thompson · 1933
Earlier work this paper cites.
A New Method of Locating the Maximum Point of An Arbitrary Multipeak Curve in the Presence of Noise
Harold J Kushner · 1964
Earlier work this paper cites.
Lipschitzian Optimization Without the Lipschitz Constant
Donald R Jones, Cary D Perttunen, and Bruce E Stuckman · 1993
Earlier work this paper cites.
Efficient Global Optimization of Expensive Black-Box Functions
Donald R. Jones, Matthias Schonlau, and William J. Welch · 1998
Earlier work this paper cites.
A Distribution Free Theory of Nonparametric Regression
László Györfi, Micael Kohler, Adam Krzyzak, and Harro Walk · 2002
Earlier work this paper cites.
Using Confidence Bounds for Exploitation-Exploration Trade-offs
Peter Auer · 2003
Earlier work this paper cites.
Slice Sampling
Radford M Neal · 2003
Earlier work this paper cites.
Topics in Optimal Transportation
Cédric Villani · 2003
Earlier work this paper cites.
Automated Antenna Design with Evolutionary Algorithms
Gregory Hornby, Al Globus, Derek Linden, and Jason Lohn · 2006
Earlier work this paper cites.
Sequential Kriging Optimization Using Multiple-fidelity Evaluations
Deng Huang, Theodore T Allen, William I Notz, and R Allen Miller · 2006
Earlier work this paper cites.
A Bayesian Model Selection Analysis of WMAP3
David Parkinson, Pia Mukherjee, and Andrew R Liddle · 2006
Earlier work this paper cites.
Gaussian Processes for Machine Learning
Carl Edward Rasmussen and Christopher KI Williams · 2006
Earlier work this paper cites.
Cosmological Constraints from the SDSS Luminous Red Galaxies
Max Tegmark, Daniel J Eisenstein, Michael A Strauss, David H Weinberg, Michael R Blanton, Joshua A Frieman, Masataka Fukugita, James E Gunn, Andrew JS Hamilton, Gillian R Knapp, et al · 2006
Earlier work this paper cites.
Scrutinizing Exotic Cosmological Models Using ESSENCE Supernova Data Combined with Other Cosmological Probes
Tamara M Davis, Edvard Mörtsell, Jesper Sollerman, Andrew C Becker, Stephanie Blondin, P Challis, Alejandro Clocchiatti, AV Filippenko, RJ Foley, Peter M Garnavich, et al · 2007
Earlier work this paper cites.
The Knowledge-Gradient Policy for Correlated Normal Beliefs
Peter Frazier, Warren Powell, and Savas Dayanik · 2009
Earlier work this paper cites.
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Niranjan Srinivas, Andreas Krause, Sham Kakade, and Matthias Seeger · 2010
Earlier work this paper cites.
Additive Gaussian Processes
David K. Duvenaud, Hannes Nickisch, and Carl Edward Rasmussen · 2011
Earlier work this paper cites.
Dealing with Asynchronicity in Parallel Gaussian Process Based Global Optimization
David Ginsbourger, Janis Janusevskis, and Rodolphe Le Riche · 2011
Earlier work this paper cites.
2D Image Registration in CT Images Using Radial Image Descriptors
Franz Graf, Hans-Peter Kriegel, Matthias Schubert, Sebastian Pölsterl, and Alexander Cavallaro · 2011
Earlier work this paper cites.
Portfolio Allocation for Bayesian Optimization
Matthew Hoffman, Eric Brochu, and Nando de Freitas · 2011
Earlier work this paper cites.
Sequential Model-based Optimization for General Algorithm Configuration
Frank Hutter, Holger H. Hoos, and Kevin Leyton-Brown · 2011
Earlier work this paper cites.
Joint Optimization and Variable Selection of High-dimensional Gaussian Processes
Bo Chen, Rui Castro, and Andreas Krause · 2012
Earlier work this paper cites.
Entropy Search for Information-efficient Global Optimization
Philipp Hennig and Christian J. Schuler · 2012
Earlier work this paper cites.
Practical Bayesian Optimization of Machine Learning Algorithms
Jasper Snoek, Hugo Larochelle, and Ryan P Adams · 2012
Earlier work this paper cites.
Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms
James Bergstra, Dan Yamins, and David D Cox · 2013
Cited alongside, same era.
High-Dimensional Gaussian Process Bandits
Josip Djolonga, Andreas Krause, and Volkan Cevher · 2013
Cited alongside, same era.
Multi-task Bayesian Optimization
Kevin Swersky, Jasper Snoek, and Ryan P Adams · 2013
Cited alongside, same era.
Bayesian Optimization in High Dimensions via Random Embeddings
Ziyu Wang, Masrour Zoghi, Frank Hutter, David Matheson, and Nando de Freitas · 2013
Cited alongside, same era.
Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures
Daniel Yamins, David Tax, and James S. Bergstra · 2013
Cited alongside, same era.
Feedback Prediction for Blogs
Krisztian Buza · 2014
Cited alongside, same era.
Bayesian Optimization for Automated Model Selection
Gustavo Malkomes, Charles Schaff, and Roman Garnett · 2016
Later among the works it cites.
Towards Automatically-tuned Neural Networks
Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, and Frank Hutter · 2016
Later among the works it cites.
Bayesian Optimization with Robust Bayesian Neural Networks
Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, and Frank Hutter · 2016
Later among the works it cites.
Data Driven Prediction Models of Energy Use of Appliances in a Low-energy House
Luis M Candanedo, Véronique Feldheim, and Dominique Deramaix · 2017
Later among the works it cites.
Discovering and Exploiting Additive Structure for Bayesian Optimization
Jacob Gardner, Chuan Guo, Kilian Weinberger, Roman Garnett, and Roger Grosse · 2017
Later among the works it cites.
Densely Connected Convolutional Networks
Gao Huang, Zhuang Liu, Kilian Q Weinberger, and Laurens van der Maaten · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Parallelizing Exploration-Exploitation Tradeoffs in Gaussian Process Bandit Optimization
Thomas Desautels, Andreas Krause, and Joel W Burdick · 2014
Cited alongside, same era.
Bayesian Optimization for Synthetic Gene Design
Javier Gonzalez, Joseph Longworth, David James, and Neil Lawrence · 2014
Cited alongside, same era.
Modular Mechanisms for Bayesian Optimization
Matthew W Hoffman and Bobak Shahriari · 2014
Cited alongside, same era.
An Entropy Search Portfolio for Bayesian Optimization
Bobak Shahriari, Ziyu Wang, Matthew W Hoffman, Alexandre Bouchard-Côté, and Nando de Freitas · 2014
Cited alongside, same era.
UJIIndoorLoc: A New Multi-building and Multi-floor Database for WLAN Fingerprint-based Indoor Localization Problems
Joaquín Torres-Sospedra, Raúl Montoliu, Adolfo Martínez-Usó, Joan P Avariento, Tomás J Arnau, Mauri Benedito-Bordonau, and Joaquín Huerta · 2014
Cited alongside, same era.
A Proactive Intelligent Decision Support System for Predicting the Popularity of Online News
Kelwin Fernandes, Pedro Vinagre, and Paulo Cortez · 2015
Cited alongside, same era.
Later among the works it cites.
Bayesian Optimization with Tree-structured Dependencies
Rodolphe Jenatton, Cedric Archambeau, Javier González, and Matthias Seeger · 2017
Later among the works it cites.
Multi-fidelity Bayesian Optimisation with Continuous Approximations
Kirthevasan Kandasamy, Gautam Dasarathy, Jeff Schneider, and Barnabás Póczos · 2017
Later among the works it cites.
Hierarchical representations for efficient architecture search
Hanxiao Liu, Karen Simonyan, Oriol Vinyals, Chrisantha Fernando, and Koray Kavukcuoglu · 2017
Later among the works it cites.
Multi-Information Source Optimization
Matthias Poloczek, Jialei Wang, and Peter Frazier · 2017
Later among the works it cites.
Improving the Expected Improvement Algorithm
Chao Qin, Diego Klabjan, and Daniel Russo · 2017
Later among the works it cites.
Calculating Luminosity Distance Versus Redshift in FLRW Cosmology via Homotopy Perturbation Method
VK Shchigolev · 2017
Later among the works it cites.
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning
Zi Wang, Chengtao Li, Stefanie Jegelka, and Pushmeet Kohli · 2017
Later among the works it cites.
Neural Architecture Search with Reinforcement Learning
Barret Zoph and Quoc V Le · 2017
Later among the works it cites.
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
Lisha Li, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, and Ameet Talwalkar · 2018
Later among the works it cites.
A Flexible Multi-Objective Bayesian Optimization Approach using Random Scalarizations
Biswajit Paria, Kirthevasan Kandasamy, and Barnabás Póczos · 2018
Later among the works it cites.
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups
Paul Rolland, Jonathan Scarlett, Ilija Bogunovic, and Volkan Cevher · 2018
Later among the works it cites.
Batched Large-scale Bayesian Optimization in High-dimensional Spaces
Zi Wang, Clement Gehring, Pushmeet Kohli, and Stefanie Jegelka · 2018
Later among the works it cites.
Random Search and Reproducibility for Neural Architecture Search
Liam Li and Ameet Talwalkar · 2019
Closest in time.
DARTS: Differentiable Architecture Search
Hanxiao Liu, Karen Simonyan, and Yiming Yang · 2019
Closest in time.
ProBO: a Framework for Using Probabilistic Programming in Bayesian Optimization
Willie Neiswanger, Kirthevasan Kandasamy, Barnabas Poczos, Jeff Schneider, and Eric Xing · 2019
Closest in time.
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes
Jialin Song, Yuxin Chen, and Yisong Yue · 2019
Closest in time.
Constrained Bayesian Optimization for Automatic Chemical Design using Variational Autoencoders
Ryan-Rhys Griffiths and José Miguel Hernández-Lobato · 2020
Closest in time.