| Hyperparameter tuning for big data using Bayesian optimisation TT Joy, S Rana, S Gupta, S Venkatesh International Conference on Pattern Recognition (ICPR), 2574-2579, 2016 | 109* | 2016 |
| Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives TT Joy, S Rana, S Gupta, S Venkatesh Knowledge-Based Systems 205, 106247, 2020 | 59 | 2020 |
| A flexible transfer learning framework for Bayesian optimization with convergence guarantee TT Joy, S Rana, S Gupta, S Venkatesh Expert Systems with Applications 115, 656-672, 2019 | 52 | 2019 |
| Batch Bayesian optimization using multi-scale search TT Joy, S Rana, S Gupta, S Venkatesh Knowledge-Based Systems 187, 104818, 2020 | 42 | 2020 |
| Flexible transfer learning framework for Bayesian optimisation TT Joy, S Rana, SK Gupta, S Venkatesh Pacific-Asia Conference on Knowledge Discovery and Data Mining, 102-114, 2016 | 22 | 2016 |
| Improving the flexibility of dynamic prosody modification using instants of significant excitation D Govind, TT Joy Circuits, Systems, and Signal Processing 35 (7), 2518-2543, 2016 | 12 | 2016 |
| Analyzing Epistemic and Aleatoric Uncertainty for Drusen Segmentation in Optical Coherence Tomography Images TT Joy, S Sedai, R Garnavi arXiv preprint arXiv:2101.08888, 2021 | 6 | 2021 |
| A corpus for differential diagnosis: an eye diseases use case AJ Yepes, DM Iraola, P Barnard, TT Joy bioRxiv, 2021.05. 10.443343, 2021 | | 2021 |
| Efficient hyperparameter tuning using Bayesian optimization T T Joy Deakin University, 2019 | | 2019 |
| Multiple Recommendation for Bayesian optimization via Multi-Scale Search TT Joy, S Rana, S Gupta, S Venkatesh 30th Annual Conference on Advances in Neural Information Processing Systems …, 2016 | | 2016 |
| Analysis of Segmental Durations and Significance of Dynamic Duration Modification for Emotion Conversion TT Joy, D Govind | | |
Svetha VenkateshAlfred Deakin Professor, Deakin University在 deakin.edu.au 的电子邮件经过验证
