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Santu Rana
Santu Rana
Associate Professor of Computer Science, Deakin University
Verified email at deakin.edu.au - Homepage
Title
Cited by
Cited by
Year
Guidelines for developing and reporting machine learning predictive models in biomedical research: a multidisciplinary view
W Luo, D Phung, T Tran, S Gupta, S Rana, C Karmakar, A Shilton, ...
Journal of medical Internet research 18 (12), e5870, 2016
3882016
High dimensional bayesian optimization using dropout
C Li, S Gupta, S Rana, V Nguyen, S Venkatesh, A Shilton
26th International Joint Conference on Artificial Intelligence, 2096--2102, 2017
902017
Rapid Bayesian optimisation for synthesis of short polymer fiber materials
C Li, D Rubín de Celis Leal, S Rana, S Gupta, A Sutti, S Greenhill, ...
Scientific reports 7 (1), 1-10, 2017
832017
High dimensional Bayesian optimization with elastic Gaussian process
S Rana, C Li, S Gupta, V Nguyen, S Venkatesh
International conference on machine learning, 2883-2891, 2017
752017
Differentially private random forest with high utility
S Rana, SK Gupta, S Venkatesh
2015 IEEE International Conference on Data Mining, 955-960, 2015
662015
Bayesian optimization for adaptive experimental design: A review
S Greenhill, S Rana, S Gupta, P Vellanki, S Venkatesh
IEEE access 8, 13937-13948, 2020
552020
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, 279-294, 2017
472017
A framework for feature extraction from hospital medical data with applications in risk prediction
T Tran, W Luo, D Phung, S Gupta, S Rana, RL Kennedy, A Larkins, ...
BMC bioinformatics 15 (1), 425, 2014
47*2014
Predicting unplanned readmission after myocardial infarction from routinely collected administrative hospital data
S Rana, T Tran, W Luo, D Phung, RL Kennedy, S Venkatesh
Australian Health Review 38 (4), 377-382, 2014
462014
Hyperparameter tuning for big data using Bayesian optimisation
TT Joy, S Rana, S Gupta, S Venkatesh
2016 23rd International Conference on Pattern Recognition (ICPR), 2574-2579, 2016
40*2016
Budgeted batch Bayesian optimization
V Nguyen, S Rana, SK Gupta, C Li, S Venkatesh
2016 IEEE 16th International Conference on Data Mining (ICDM), 1107-1112, 2016
332016
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
282019
Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset
W Luo, T Nguyen, M Nichols, T Tran, S Rana, S Gupta, D Phung, ...
PloS one 10 (5), e0125602, 2015
282015
Exploration enhanced expected improvement for bayesian optimization
J Berk, V Nguyen, S Gupta, S Rana, S Venkatesh
joint european conference on machine learning and knowledge discovery in …, 2018
262018
A unified tensor framework for face recognition
S Rana, W Liu, M Lazarescu, S Venkatesh
Pattern Recognition 42 (11), 2850-2862, 2009
252009
Recognising faces in unseen modes: a tensor based approach
S Rana, W Liu, M Lazarescu, S Venkatesh
2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008
232008
Coupling machine learning with 3D bioprinting to fast track optimisation of extrusion printing
K Ruberu, M Senadeera, S Rana, S Gupta, J Chung, Z Yue, S Venkatesh, ...
Applied Materials Today 22, 100914, 2021
222021
Regret bounds for transfer learning in Bayesian optimisation
A Shilton, S Gupta, S Rana, S Venkatesh
Artificial Intelligence and Statistics, 307-315, 2017
222017
Batch Bayesian optimization using multi-scale search
TT Joy, S Rana, S Gupta, S Venkatesh
Knowledge-Based Systems 187, 104818, 2020
202020
Multi-objective Bayesian optimisation with preferences over objectives
M Abdolshah, A Shilton, S Rana, S Gupta, S Venkatesh
Advances in Neural Information Processing Systems 32, 2019
202019
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