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Bobak Shahriari
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Taking the human out of the loop: A review of Bayesian optimization
B Shahriari, K Swersky, Z Wang, RP Adams, N De Freitas
Proceedings of the IEEE 104 (1), 148-175, 2015
51222015
Critic regularized regression
Z Wang, A Novikov, K Zolna, JS Merel, JT Springenberg, SE Reed, ...
Advances in Neural Information Processing Systems 33, 7768-7778, 2020
2852020
Acme: A research framework for distributed reinforcement learning
MW Hoffman, B Shahriari, J Aslanides, G Barth-Maron, N Momchev, ...
arXiv preprint arXiv:2006.00979, 2020
2352020
On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning
M Hoffman, B Shahriari, N Freitas
Artificial Intelligence and Statistics, 365-374, 2014
1712014
Making efficient use of demonstrations to solve hard exploration problems
TL Paine, C Gulcehre, B Shahriari, M Denil, M Hoffman, H Soyer, ...
arXiv preprint arXiv:1909.01387, 2019
882019
An entropy search portfolio for Bayesian optimization
B Shahriari, Z Wang, MW Hoffman, A Bouchard-Côté, N de Freitas
arXiv preprint arXiv:1406.4625, 2014
782014
Unbounded Bayesian optimization via regularization
B Shahriari, A Bouchard-Côté, N Freitas
Artificial intelligence and statistics, 1168-1176, 2016
772016
Gemma: Open models based on gemini research and technology
G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ...
arXiv preprint arXiv:2403.08295, 2024
592024
Modular mechanisms for Bayesian optimization
MW Hoffman, B Shahriari
NIPS workshop on Bayesian optimization, 1-5, 2014
362014
Do we need “harmless” Bayesian optimization and “first-order” Bayesian optimization
MO Ahmed, B Shahriari, M Schmidt
NIPS BayesOpt, 2016
342016
Heteroscedastic treed bayesian optimisation
JAM Assael, Z Wang, B Shahriari, N de Freitas
arXiv preprint arXiv:1410.7172, 2014
282014
On multi-objective policy optimization as a tool for reinforcement learning
A Abdolmaleki, SH Huang, G Vezzani, B Shahriari, JT Springenberg, ...
arXiv preprint arXiv:2106.08199, 2021
242021
Which learning algorithms can generalize identity-based rules to novel inputs?
P Tupper, B Shahriari
arXiv preprint arXiv:1605.04002, 2016
92016
A combined finite element and Bayesian optimization framework for shape optimization in spectral geometry
S Dominguez, N Nigam, B Shahriari
Computers & Mathematics with Applications 74 (11), 2874-2896, 2017
72017
Practical Bayesian optimization with application to tuning machine learning algorithms
B Shahriari
University of British Columbia, 2016
62016
The modified Cahn-Hilliard equation on general surfaces
B Shahriari
Simon Fraser University, 2010
62010
Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach
B Shahriari, A Abdolmaleki, A Byravan, A Friesen, S Liu, JT Springenberg, ...
arXiv preprint arXiv:2204.10256, 2022
32022
Knowledge Transfer from Teachers to Learners in Growing-Batch Reinforcement Learning
P Emedom-Nnamdi, AL Friesen, B Shahriari, N de Freitas, MW Hoffman
arXiv preprint arXiv:2305.03870, 2023
2023
Bayesian optimization: an introduction, review (and demo)
B Shahriari
2016
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Articles 1–19