Bayesian Optimization: Publications
Book chapters
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[1]
Active Preference Learning with Discrete Choice Data
Brochu Eric‚ Nando de Freitas and Abhijeet Ghosh
In J.C. Platt‚ D. Koller‚ Y. Singer and S. Roweis, editors, Advances in Neural Information Processing Systems 20. Pages 409–416. MIT Press, Cambridge‚ MA. 2007.
Details about Active Preference Learning with Discrete Choice Data | BibTeX data for Active Preference Learning with Discrete Choice Data | Download (pdf) of Active Preference Learning with Discrete Choice Data
Journal papers
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[1]
Self−Avoiding Random Dynamics on Integer Complex Systems
Firas Hamze‚ Ziyu Wang and Nando de Freitas
In ACM Transactions on Modelling and Computer Simulation. Vol. 23. No. 1. Pages 9:1–9:25. 2013.
Details about Self−Avoiding Random Dynamics on Integer Complex Systems | BibTeX data for Self−Avoiding Random Dynamics on Integer Complex Systems | DOI (10.1145/2414416.2414790) | Link to Self−Avoiding Random Dynamics on Integer Complex Systems
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[2]
Adaptive MCMC with Bayesian Optimization
Nimalan Mahendran‚ Ziyu Wang‚ Firas Hamze and Nando de Freitas
In Journal of Machine Learning Research − Proceedings Track for Artificial Intelligence and Statistics (AISTATS). Vol. 22. Pages 751–760. 2012.
Details about Adaptive MCMC with Bayesian Optimization | BibTeX data for Adaptive MCMC with Bayesian Optimization | Link to Adaptive MCMC with Bayesian Optimization
Conference papers
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[1]
Bayesian Multi−Scale Optimistic Optimization
Ziyu Wang‚ Babak Shakibi‚ Lin Jin and Nando de Freitas
In Artificial Intelligence and Statistics (AISTATS). Pages 1005−1014. 2014.
Details about Bayesian Multi−Scale Optimistic Optimization | BibTeX data for Bayesian Multi−Scale Optimistic Optimization | Download (pdf) of Bayesian Multi−Scale Optimistic Optimization
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[2]
Bayesian Optimization with an Empirical Hardness Model for Approximate Nearest Neighbour Search
Julieta Martinez‚ James Little and Nando de Freitas
In IEEE Winter Conference on Applications of Computer Vision (WACV). 2014.
Details about Bayesian Optimization with an Empirical Hardness Model for Approximate Nearest Neighbour Search | BibTeX data for Bayesian Optimization with an Empirical Hardness Model for Approximate Nearest Neighbour Search | Download (pdf) of Bayesian Optimization with an Empirical Hardness Model for Approximate Nearest Neighbour Search
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[3]
On correlation and budget constraints in model−based bandit optimization with application to automatic machine learning
Bobak Shahriari‚ Matthew Hoffman and Nando de Freitas
In Artificial Intelligence and Statistics (AISTATS). Pages 365–374. 2014.
Details about On correlation and budget constraints in model−based bandit optimization with application to automatic machine learning | BibTeX data for On correlation and budget constraints in model−based bandit optimization with application to automatic machine learning | Download (pdf) of On correlation and budget constraints in model−based bandit optimization with application to automatic machine learning
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[4]
Adaptive Hamiltonian and Riemann Manifold Monte Carlo Samplers
Ziyu Wang‚ Shakir Mohamed and Nando de Freitas
In International Conference on Machine Learning (ICML). Pages 1462–1470. 2013.
JMLR &CPW 28 (3): 1462–1470‚ 2013
Details about Adaptive Hamiltonian and Riemann Manifold Monte Carlo Samplers | BibTeX data for Adaptive Hamiltonian and Riemann Manifold Monte Carlo Samplers | Download (pdf) of Adaptive Hamiltonian and Riemann Manifold Monte Carlo Samplers
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[5]
Bayesian Optimization in High Dimensions via Random Embeddings
Ziyu Wang‚ Masrour Zoghi‚ Frank Hutter‚ David Matheson and Nando de Freitas
In International Joint Conferences on Artificial Intelligence (IJCAI) − Distinguished Paper Award. 2013.
Details about Bayesian Optimization in High Dimensions via Random Embeddings | BibTeX data for Bayesian Optimization in High Dimensions via Random Embeddings | Download (pdf) of Bayesian Optimization in High Dimensions via Random Embeddings
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[6]
Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations
Nando de Freitas‚ Alex Smola and Masrour Zoghi
In International Conference on Machine Learning (ICML). 2012.
Details about Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations | BibTeX data for Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations | Link to Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations
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[7]
A Bayesian interactive optimization approach to procedural animation design
Eric Brochu‚ Tyson Brochu and Nando de Freitas
In Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation. Pages 103–112. Aire−la−Ville‚ Switzerland‚ Switzerland. 2010. Eurographics Association.
Details about A Bayesian interactive optimization approach to procedural animation design | BibTeX data for A Bayesian interactive optimization approach to procedural animation design | Link to A Bayesian interactive optimization approach to procedural animation design
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[8]
Preference galleries for material design
Eric Brochu‚ Abhijeet Ghosh and Nando de Freitas
In ACM SIGGRAPH 2007 posters − Winner of the Student RC competition at SIGGRAPH.. New York‚ NY‚ USA. 2007. ACM.
Details about Preference galleries for material design | BibTeX data for Preference galleries for material design | DOI (10.1145/1280720.1280834) | Link to Preference galleries for material design
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[9]
Active Policy Learning for Robot Planning and Exploration under Uncertainty
Ruben Martinez−Cantin‚ Nando de Freitas‚ Arnaud Doucet and Jose Castellanos
In Proceedings of Robotics: Science and Systems. Atlanta‚ GA‚ USA. June, 2007.
Details about Active Policy Learning for Robot Planning and Exploration under Uncertainty | BibTeX data for Active Policy Learning for Robot Planning and Exploration under Uncertainty | Link to Active Policy Learning for Robot Planning and Exploration under Uncertainty
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[10]
SMC Samplers for Bayesian Optimal Nonlinear Design
Hendrik Kuck‚ N. de Freitas and Arnaud Doucet
In IEEE Nonlinear Statistical Signal Processing Workshop. Pages 99–102. 2006.
Details about SMC Samplers for Bayesian Optimal Nonlinear Design | BibTeX data for SMC Samplers for Bayesian Optimal Nonlinear Design | Download (pdf) of SMC Samplers for Bayesian Optimal Nonlinear Design
Technical reports
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[1]
An Entropy Search Portfolio for Bayesian Optimization
Bobak Shahriari‚ Ziyu Wang‚ Matthew W. Hoffman‚ Alexandre Bouchard−Cote and Nando de Freitas
No. arXiv:1406.4625. University of Oxford. 2014.
Details about An Entropy Search Portfolio for Bayesian Optimization | BibTeX data for An Entropy Search Portfolio for Bayesian Optimization | Link to An Entropy Search Portfolio for Bayesian Optimization