Santu Rana
Santu Rana
Associate Professor of Computer Science, Deakin University
Verified email at - Homepage
Cited by
Cited by
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
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
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
Differentially private random forest with high utility
S Rana, SK Gupta, S Venkatesh
2015 IEEE International Conference on Data Mining, 955-960, 2015
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
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
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
A unified tensor framework for face recognition
S Rana, W Liu, M Lazarescu, S Venkatesh
Pattern Recognition 42 (11), 2850-2862, 2009
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
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
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
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
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
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
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
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
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
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
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
Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records
C Li, S Rana, D Phung, S Venkatesh
Knowledge-Based Systems 99, 168-182, 2016
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