Vu Nguyen
Vu Nguyen
Amazon
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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
662017
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
562017
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
362014
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
302017
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
262016
Nonparametric budgeted stochastic gradient descent
T Le, V Nguyen, TD Nguyen, D Phung
Artificial Intelligence and Statistics (AISTATS), 654-572, 2016
242016
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
212020
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
182018
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
142019
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
142016
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
142016
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
132018
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
132018
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
132017
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
132016
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
132012
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Articles 1–20