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
Sunil GuptaAssociate Professor, Deakin UniversityVerified email at deakin.edu.au
Trung LeFaculty of Information Technology, Monash University, AustraliaVerified email at monash.edu
Tu Dinh NguyenLead Research Scientist, Trusting SocialVerified email at trustingsocial.com
Cheng LiNational University of Singapore, SingaporeVerified email at comp.nus.edu.sg
Michael A OsborneProfessor of Machine Learning, University of OxfordVerified email at robots.ox.ac.uk
Hung BuiResearch Scientist, Google DeepMindVerified email at google.com
Stephen RobertsProfessor of Engineering Science (Machine Learning, Information Engineering), University of OxfordVerified email at robots.ox.ac.uk
XuanLong NguyenUniversity of MichiganVerified email at umich.edu
Alistair ShiltonApplied Artificial Intelligence Institute (A²I²), Deakin UniversityVerified email at deakin.edu.au
G A D BriggsProfessor of Nanomaterials, University of OxfordVerified email at materials.ox.ac.uk
Dominic LennonGraduate Student, University of Oxford, MaterialsVerified email at materials.ox.ac.uk
Dino SejdinovicUniversity of OxfordVerified email at stats.ox.ac.uk
Natalia AresOxford UniversityVerified email at materials.ox.ac.uk
Sonny PhamCurtin UniversityVerified email at curtin.edu.au
Binxin RuDPhil Student, University of OxfordVerified email at robots.ox.ac.uk
Julian BerkPhD Student, Deakin UniversityVerified email at deakin.edu.au
Ngoc-Trung TranSUTDVerified email at sutd.edu.sg
Florian VigneauOxford University, Materials departmentVerified email at materials.ox.ac.uk

Vu Nguyen

University of Oxford

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

Bayesian Optimization 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	61	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	53	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
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
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	25	2017
Budgeted batch bayesian optimization V Nguyen, S Rana, SK Gupta, C Li, S Venkatesh IEEE International Conference on Data Mining (ICDM), 1107-1112, 2016	24	2016
Nonparametric budgeted stochastic gradient descent T Le, V Nguyen, TD Nguyen, D Phung Artificial Intelligence and Statistics (AISTATS), 654-572, 2016	23	2016
Knowing the what but not the where in Bayesian optimization V Nguyen, MA Osborne International Conference on Machine Learning (ICML), 7317-7326, 2020	17*	2020
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
Bayesian optimization for accelerating hyper-parameter tuning V Nguyen 2019 IEEE Second International Conference on Artificial Intelligence and …, 2019	13	2019
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
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
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	12	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	12	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	12	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	12	2017
Bayesian optimization in weakly specified search space V Nguyen, S Gupta, S Rane, C Li, S Venkatesh IEEE International Conference on Data Mining (ICDM), 347-356, 2017	11	2017
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	11	2017

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