Santu Rana
Santu Rana
Associate Professor of Computer Science, Deakin University
Verified email at deakin.edu.au
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), e323, 2016
1492016
Rapid Bayesian optimisation for synthesis of short polymer fiber materials
C Li, DR de Celis Leal, S Rana, S Gupta, A Sutti, S Greenhill, T Slezak, ...
Scientific reports 7 (1), 1-10, 2017
482017
Differentially private random forest with high utility
S Rana, SK Gupta, S Venkatesh
2015 IEEE International Conference on Data Mining, 955-960, 2015
402015
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
382014
High dimensional bayesian optimization using dropout
C Li, S Gupta, S Rana, V Nguyen, S Venkatesh, A Shilton
arXiv preprint arXiv:1802.05400, 2018
372018
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
362017
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
322014
A unified tensor framework for face recognition
S Rana, W Liu, M Lazarescu, S Venkatesh
Pattern Recognition 42 (11), 2850-2862, 2009
232009
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
222016
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
212008
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
182016
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
172017
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
162015
Regret bounds for transfer learning in Bayesian optimisation
A Shilton, S Gupta, S Rana, S Venkatesh
AISTATS 2017: Machine Learning Research: Proceedings of the 20th Artificial …, 2017
132017
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
132016
Large-scale statistical modeling of motion patterns: a Bayesian nonparametric approach
S Rana, D Phung, S Pham, S Venkatesh
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and …, 2012
132012
Accelerating experimental design by incorporating experimenter hunches
C Li, S Rana, S Gupta, V Nguyen, S Venkatesh, A Sutti, D Rubin, T Slezak, ...
arXiv preprint arXiv:1907.09065, 2019
122019
A Bayesian nonparametric approach for multi-label classification
V Nguyen, S Gupta, S Rana, C Li, S Venkatesh
Asian conference on machine learning, 254-269, 2016
122016
Web search activity data accurately predict population chronic disease risk in the USA
T Nguyen, T Tran, W Luo, S Gupta, S Rana, D Phung, M Nichols, L Millar, ...
J Epidemiol Community Health 69 (7), 693-699, 2015
122015
A predictive framework for modeling healthcare data with evolving clinical interventions
S Rana, S Gupta, D Phung, S Venkatesh
Statistical Analysis and Data Mining: The ASA Data Science Journal 8 (3 …, 2015
122015
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Articles 1–20