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Ryan Turner
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Conference and Workshop Papers
- 2020
- [c6]Ryan Turner, David Eriksson, Michael McCourt, Juha Kiili, Eero Laaksonen, Zhen Xu, Isabelle Guyon:
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020. NeurIPS (Competition and Demos) 2020: 3-26 - 2019
- [c5]David Eriksson, Michael Pearce, Jacob R. Gardner, Ryan Turner, Matthias Poloczek:
Scalable Global Optimization via Local Bayesian Optimization. NeurIPS 2019: 5497-5508 - 2018
- [c4]Ryan Turner, Brady Neal:
How well does your sampler really work? UAI 2018: 73-82 - 2017
- [c3]Jason Mayer, Ryan Turner:
3rd Harmonic current in a generator neutral earthing resistor connected to a large cable network. IAS 2017: 1-5 - 2016
- [c2]Daniel S. Brown, Ryan Turner, Oliver Hennigh, Steven Loscalzo:
Discovery and Exploration of Novel Swarm Behaviors Given Limited Robot Capabilities. DARS 2016: 447-460 - [c1]Ryan Turner:
A model explanation system. MLSP 2016: 1-6
Informal and Other Publications
- 2023
- [i5]Daniel Kharitonov, Ryan Turner:
Dataset Factory: A Toolchain For Generative Computer Vision Datasets. CoRR abs/2309.11608 (2023) - 2021
- [i4]Ryan Turner, David Eriksson, Michael McCourt, Juha Kiili, Eero Laaksonen, Zhen Xu, Isabelle Guyon:
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020. CoRR abs/2104.10201 (2021) - 2019
- [i3]David Eriksson, Michael Pearce, Jacob R. Gardner, Ryan Turner, Matthias Poloczek:
Scalable Global Optimization via Local Bayesian Optimization. CoRR abs/1910.01739 (2019) - 2017
- [i2]David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron C. Courville:
Bayesian Hypernetworks. CoRR abs/1710.04759 (2017) - 2016
- [i1]Ryan Turner:
A Model Explanation System: Latest Updates and Extensions. CoRR abs/1606.09517 (2016)
Coauthor Index
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