| 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 | 95 | 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 | 79 | 2017 |
| 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 | 54 | 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 | 47 | 2020 |
| Budgeted batch bayesian optimization V Nguyen, S Rana, SK Gupta, C Li, S Venkatesh IEEE International Conference on Data Mining (ICDM), 1107-1112, 2016 | 43* | 2016 |
| Bayesian optimization for accelerating hyper-parameter tuning V Nguyen IEEE Second International Conference on Artificial Intelligence and …, 2019 | 38 | 2019 |
| 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 | 37 | 2014 |
| Exploration Enhanced Expected Improvement for Bayesian Optimization J Berk, V Nguyen, S Gupta, S Rana, S Venkatesh European Conference on Machine Learning (ECML), 2018 | 32 | 2018 |
| Provably efficient online hyperparameter optimization with population-based bandits J Parker-Holder, V Nguyen, SJ Roberts Advances in Neural Information Processing Systems 33, 17200-17211, 2020 | 28 | 2020 |
| Dual Space Gradient Descent for Online Learning T Le, T Nguyen, V Nguyen, D Phung Advances in Neural Information Processing Systems (NeurIPS), 4583-4591, 2016 | 28 | 2016 |
| Nonparametric budgeted stochastic gradient descent T Le, V Nguyen, TD Nguyen, D Phung Artificial Intelligence and Statistics (AISTATS), 654-572, 2016 | 27 | 2016 |
| Knowing the what but not the where in Bayesian optimization V Nguyen, MA Osborne International Conference on Machine Learning (ICML), 7317-7326, 2020 | 26 | 2020 |
| Quantum device fine-tuning using unsupervised embedding learning NM van Esbroeck, DT Lennon, H Moon, V Nguyen, F Vigneau, ... New Journal of Physics, 2020 | 20 | 2020 |
| 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 | 20 | 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 | 19* | 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 | 19 | 2017 |
| Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning S Kessler, V Nguyen, S Zohren, S Roberts Uncertainty in Artificial Intelligence (UAI), 2021 | 17* | 2021 |
| 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 | 17 | 2018 |
| 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 | 17 | 2016 |
| 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 | 16 | 2018 |
Svetha VenkateshProfessor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
