| 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 | 51 | 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 | 48 | 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 | 35 | 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 |
| Nonparametric budgeted stochastic gradient descent T Le, V Nguyen, TD Nguyen, D Phung Artificial Intelligence and Statistics (AISTATS), 654-572, 2016 | 24 | 2016 |
| Budgeted batch bayesian optimization V Nguyen, S Rana, SK Gupta, C Li, S Venkatesh IEEE International Conference on Data Mining (ICDM), 1107-1112, 2016 | 23 | 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 | 22 | 2017 |
| 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 | 16 | 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 |
| 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 |
| 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 | 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 |
| 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 |
| 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 | 12 | 2017 |
| 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 | 11 | 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 | 10 | 2020 |
| Bayesian optimization for accelerating hyper-parameter tuning V Nguyen 2019 IEEE Second International Conference on Artificial Intelligence and …, 2019 | 10 | 2019 |
| 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 | 10 | 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 | 9 | 2016 |
| SECC: Simultaneous extraction of context and community from pervasive signals T Nguyen, V Nguyen, FD Salim, D Phung IEEE International Conference on Pervasive Computing and Communications …, 2016 | 9 | 2016 |
Svetha VenkateshProfessor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
