Vu Nguyen

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Svetha VenkateshDeakin Distinguished Professor, 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
Anton van den HengelDirector of the Centre for Augmented Reasoning at AIML.Verified email at adelaide.edu.au
Binxin RuDPhil Student, University of OxfordVerified email at robots.ox.ac.uk
Hung BuiResearch Scientist, Google DeepMindVerified email at google.com
Dino SejdinovicProfessor of Statistical Machine Learning, University of AdelaideVerified email at adelaide.edu.au
Huong HaSenior Lecturer of Computer Science, School of Computing Technologies, RMITVerified email at rmit.edu.au
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 HutterELLIS Institute & Professor, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Xingyou (Richard) SongSenior Research Scientist, Google DeepMindVerified email at google.com
Theresa EimerRL Team Lead, Leibniz Universität HannoverVerified email at ai.uni-hannover.de
Xingchen WanGoogleVerified 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
Thalaiyasingam AjanthanPluralis Research | Australian National UniversityVerified email at anu.edu.au

Vu Nguyen

Senior ML Scientist, Amazon

Verified email at robots.ox.ac.uk - Homepage

Bayesian Optimisation Machine Learning AutoML


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Bayesian optimization for accelerating hyper-parameter tuning V Nguyen IEEE Second International Conference on Artificial Intelligence and …, 2019	156	2019
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	130	2017
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	127	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	105	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	103	2022
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	96	2017
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	95	2022
Provably efficient online hyperparameter optimization with population-based bandits J Parker-Holder, V Nguyen, SJ Roberts Advances in Neural Information Processing Systems (NeurIPS) 33, 17200-17211, 2020	85	2020
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	60	2021
Budgeted batch bayesian optimization V Nguyen, S Rana, SK Gupta, C Li, S Venkatesh IEEE International Conference on Data Mining (ICDM), 1107-1112, 2016	58*	2016
Exploration Enhanced Expected Improvement for Bayesian Optimization J Berk, V Nguyen, S Gupta, S Rana, S Venkatesh European Conference on Machine Learning (ECML), 2018	56	2018
Knowing the what but not the where in Bayesian optimization V Nguyen, MA Osborne International Conference on Machine Learning (ICML), 7317-7326, 2020	51	2020
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	46	2014
Quantum device fine-tuning using unsupervised embedding learning NM van Esbroeck, DT Lennon, H Moon, V Nguyen, F Vigneau, ... New Journal of Physics, 2020	40	2020
Bayesian optimization for iterative learning V Nguyen, S Schulze, MA Osborne Advances in Neural Information Processing Systems (NeurIPS), 2020	37	2020
Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning S Kessler, V Nguyen, S Zohren, S Roberts Uncertainty in Artificial Intelligence (UAI), 2021	35*	2021
Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation S Gopakumar, S Gupta, S Rana, V Nguyen, S Venkatesh Advances in Neural Information Processing Systems (NeurIPS), 5470-5478, 2018	34	2018
Optimal transport kernels for sequential and parallel neural architecture search V Nguyen, T Le, M Yamada, MA Osborne International Conference on Machine Learning (ICML), 8084-8095, 2021	33	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	33	2018
Accelerating experimental design by incorporating experimenter hunches C Li, S Rana, S Gupta, V Nguyen, S Venkatesh, A Sutti, D Rubin, T Slezak, ... IEEE International Conference on Data Mining (ICDM), 257--266, 2018	30	2018

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