Vu Nguyen

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Svetha VenkateshProfessor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Dinh PhungProfessor, Monash UniversityVerified email at monash.edu
Michael A OsborneProfessor of Machine Learning, University of OxfordVerified email at robots.ox.ac.uk
Stephen RobertsProfessor of Engineering Science (Machine Learning, Information Engineering), University of OxfordVerified email at robots.ox.ac.uk
Jack Parker-HolderGoogle DeepMind, UCLVerified email at google.com
Binxin RuDPhil Student, University of OxfordVerified email at robots.ox.ac.uk
Dino SejdinovicProfessor, University of AdelaideVerified email at adelaide.edu.au
Hung BuiResearch Scientist, Google DeepMindVerified email at google.com
Natalia AresOxford UniversityVerified email at eng.ox.ac.uk
G A D BriggsProfessor of Nanomaterials, University of OxfordVerified email at materials.ox.ac.uk
Anton van den HengelDirector of Applied Science at Amazon and Director of the Centre for Augmented Reasoning at AIML.Verified email at adelaide.edu.au
XuanLong NguyenUniversity of MichiganVerified email at umich.edu
Roi Cohen KadoshUniversity of SurreyVerified email at surrey.ac.uk
Marius LindauerLeibniz University Hannover (Germany), Institute of Artificial Intelligence LUH|AI, L3S ResearchVerified email at ai.uni-hannover.de
André BiedenkappUniversity of FreiburgVerified email at cs.uni-freiburg.de
Aleksandra FaustGoogle DeepMind, Mountain View, CAVerified email at google.com
Frank HutterProfessor of Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Xingyou (Richard) SongSenior Research Scientist, Google DeepMind (Brain Team)Verified email at google.com
Theresa EimerDoctoral Researcher, Leibniz Universität HannoverVerified email at ai.uni-hannover.de
Xingchen WanUniversity of Oxford, GoogleVerified email at google.com

Vu Nguyen

Amazon

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Bayesian Optimisation Machine Learning AutoML


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High Dimensional Bayesian Optimization Using Dropout C Li, S Gupta, S Rana, V Nguyen, S Venkatesh, A Shilton International Joint Conference on Artificial Intelligence (IJCAI), 2096-2102, 2017	136	2017
High Dimensional Bayesian Optimization with Elastic Gaussian Process S Rana, C Li, S Gupta, V Nguyen, S Venkatesh International Conference on Machine Learning (ICML), 2883-2891, 2017	106	2017
Bayesian optimization for accelerating hyper-parameter tuning V Nguyen IEEE Second International Conference on Artificial Intelligence and …, 2019	95	2019
Regret for expected improvement over the best-observed value and stopping condition V Nguyen, S Gupta, S Rana, C Li, S Venkatesh Asian Conference on Machine Learning (ACML), 279-294, 2017	75	2017
Bayesian optimisation over multiple continuous and categorical inputs B Ru, AS Alvi, V Nguyen, MA Osborne, SJ Roberts International Conference on Machine Learning (ICML), 8276-8285, 2020	73	2020
Provably efficient online hyperparameter optimization with population-based bandits J Parker-Holder, V Nguyen, SJ Roberts Advances in Neural Information Processing Systems 33, 17200-17211, 2020	60	2020
Automated reinforcement learning (autorl): A survey and open problems J Parker-Holder, R Rajan, X Song, A Biedenkapp, Y Miao, T Eimer, ... Journal of Artificial Intelligence Research 74, 517-568, 2022	54	2022
Budgeted batch bayesian optimization V Nguyen, S Rana, SK Gupta, C Li, S Venkatesh IEEE International Conference on Data Mining (ICDM), 1107-1112, 2016	51*	2016
Bayesian nonparametric multilevel clustering with group-level contexts V Nguyen, D Phung, XL Nguyen, S Venkatesh, HH Bui International Conference on Machine Learning (ICML), 288-296, 2014	45	2014
Exploration Enhanced Expected Improvement for Bayesian Optimization J Berk, V Nguyen, S Gupta, S Rana, S Venkatesh European Conference on Machine Learning (ECML), 2018	42	2018
Knowing the what but not the where in Bayesian optimization V Nguyen, MA Osborne International Conference on Machine Learning (ICML), 7317-7326, 2020	40	2020
Retrieval Augmented Classification for Long-Tail Visual Recognition A Long, W Yin, T Ajanthan, V Nguyen, P Purkait, R Garg, A Blair, C Shen, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022	38	2022
Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces X Wan, V Nguyen, H Ha, B Ru, C Lu, MA Osborne International Conference on Machine Learning (ICML), 2021	36	2021
Filtering Bayesian optimization approach in weakly specified search space V Nguyen, S Gupta, S Rana, C Li, S Venkatesh Knowledge and Information Systems 60 (1), 385-413, 2018	31	2018
Nonparametric budgeted stochastic gradient descent T Le, V Nguyen, TD Nguyen, D Phung Artificial Intelligence and Statistics (AISTATS), 654-572, 2016	28	2016
Dual Space Gradient Descent for Online Learning T Le, T Nguyen, V Nguyen, D Phung Advances in Neural Information Processing Systems (NeurIPS), 4583-4591, 2016	28	2016
Gogp: Fast online regression with gaussian processes T Le, K Nguyen, V Nguyen, TD Nguyen, D Phung IEEE International Conference on Data Mining (ICDM), 257-266, 2017	27*	2017
Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning S Kessler, V Nguyen, S Zohren, S Roberts Uncertainty in Artificial Intelligence (UAI), 2021	26*	2021
Quantum device fine-tuning using unsupervised embedding learning NM van Esbroeck, DT Lennon, H Moon, V Nguyen, F Vigneau, ... New Journal of Physics, 2020	26	2020
Bayesian optimization for iterative learning V Nguyen, S Schulze, MA Osborne Advances in Neural Information Processing Systems (NeurIPS), 2020	25	2020

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