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
Hung BuiResearch Scientist, Google DeepMindVerified email at google.com
XuanLong NguyenUniversity of MichiganVerified email at umich.edu
Dominic LennonGraduate Student, University of Oxford, MaterialsVerified email at materials.ox.ac.uk
Dino SejdinovicUniversity of OxfordVerified email at stats.ox.ac.uk
Alistair ShiltonApplied Artificial Intelligence Institute (A²I²), Deakin UniversityVerified email at deakin.edu.au
Binxin RuDPhil Student, University of OxfordVerified email at robots.ox.ac.uk
G A D BriggsProfessor of Nanomaterials, University of OxfordVerified email at materials.ox.ac.uk
Natalia AresOxford UniversityVerified email at materials.ox.ac.uk
Julian BerkPostdoctoral research fellow, Deakin UniversityVerified email at deakin.edu.au
Jack Parker-HolderDPhil Student, University of OxfordVerified email at robots.ox.ac.uk
Sonny PhamCurtin UniversityVerified email at curtin.edu.au
Florian VigneauOxford University, Materials departmentVerified email at materials.ox.ac.uk
Leon CamenzindPost-Doc, University of BaselVerified email at unibas.ch
Liuqi YuUniversity of Maryland, College ParkVerified email at lps.umd.edu
Flora SalimData Science, School of Computing Technologies, RMIT UniversityVerified email at rmit.edu.au
Samuel KesslerUniversity of OxfordVerified email at robots.ox.ac.uk

Vu Nguyen

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Bayesian Optimization Machine Learning AutoML


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	66	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	56	2017
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	36	2014
Budgeted batch bayesian optimization V Nguyen, S Rana, SK Gupta, C Li, S Venkatesh IEEE International Conference on Data Mining (ICDM), 1107-1112, 2016	31*	2016
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	30	2017
Dual Space Gradient Descent for Online Learning T Le, T Nguyen, V Nguyen, D Phung Advances in Neural Information Processing Systems (NIPS), 4583-4591, 2016	26	2016
Nonparametric budgeted stochastic gradient descent T Le, V Nguyen, TD Nguyen, D Phung Artificial Intelligence and Statistics (AISTATS), 654-572, 2016	24	2016
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	21	2020
Knowing the what but not the where in Bayesian optimization V Nguyen, MA Osborne International Conference on Machine Learning (ICML), 7317-7326, 2020	18*	2020
Exploration Enhanced Expected Improvement for Bayesian Optimization J Berk, V Nguyen, S Gupta, S Rana, S Venkatesh European Conference on Machine Learning (ECML), 2018	18	2018
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	15*	2017
Bayesian optimization for accelerating hyper-parameter tuning V Nguyen IEEE Second International Conference on Artificial Intelligence and …, 2019	14	2019
A Bayesian nonparametric approach for multi-label classification V Nguyen, S Gupta, S Rana, C Li, S Venkatesh Asian Conference on Machine Learning (ACML), 254-269, 2016	14	2016
Budgeted Semi-supervised Support Vector Machine. T Le, P Duong, M Dinh, TD Nguyen, V Nguyen, DQ Phung Uncertainty in Artificial Intelligence (UAI), 377-386, 2016	14	2016
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	13	2018
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	13	2018
Approximation vector machines for large-scale online learning T Le, TD Nguyen, V Nguyen, D Phung The Journal of Machine Learning Research (JMLR) 18 (1), 3962-4016, 2017	13	2017
One-pass logistic regression for label-drift and large-scale classification on distributed systems V Nguyen, TD Nguyen, T Le, S Venkatesh, D Phung IEEE International Conference on Data Mining (ICDM), 1113-1118, 2016	13	2016
Distributed data augmented support vector machine on spark TD Nguyen, V Nguyen, T Le, D Phung International Conference on Pattern Recognition (ICPR), 2016, 498-503, 2016	13*	2016
Conditionally dependent Dirichlet processes for modelling naturally correlated data sources D Phung, XL Nguyen, H Bui, V Nguyen, S Venkatesh Deakin University, School of Information Technology, Pattern Recognition and …, 2012	13	2012

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