Santu Rana

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Svetha VenkateshDeakin Distinguished Professor, Deakin UniversityVerified email at deakin.edu.au
Sunil GuptaProfessor, Head of AI Optimization and Materials Discovery, Deakin UniversityVerified email at deakin.edu.au
Alistair ShiltonApplied Artificial Intelligence Institute (A²I²), Deakin UniversityVerified email at deakin.edu.au
Cheng LiNational University of Singapore, SingaporeVerified email at comp.nus.edu.sg
Truyen TranProfessor | Head of AI, Health and Science @ Deakin UniversityVerified email at deakin.edu.au
Dinh PhungProfessor, Monash UniversityVerified email at monash.edu
Vu NguyenSenior ML Scientist, AmazonVerified email at robots.ox.ac.uk
Wei LuoDeakin UniversityVerified email at deakin.edu.au
Stewart GreenhillDeakin UniversityVerified email at deakin.edu.au
Pratibha VellankiDeakin University, AustraliaVerified email at research.deakin.edu.au
Alessandra SuttiDeakin University, Institute for Frontier MaterialsVerified email at deakin.edu.au
HARIPRIYA HARIKUMARResearch Fellow, University of Manchester, UKVerified email at deakin.edu.au
Majid AbdolshahMachine Learning Scientist @ AmazonVerified email at amazon.com
Tinu Theckel JoyIBM ResearchVerified email at ibm.com
David Rubín de Celis LealAssociate Research FellowVerified email at deakin.edu.au
Michael BerkDeakin UniversityVerified email at deakin.edu.au
Thin NguyenSenior Research Lecturer, Deakin University, AustraliaVerified email at deakin.edu.au
Anil RamachandranData Scientist at KeepFlying (a CBMM Company) | Aviation DSaaS | The Aviation Digital FinTwin® | PhDVerified email at keepflying.aero
Steven AllenderGlobal Centre for Preventive Health and Nutrition (GLOBE), WHO Collaborating Centre for ObesityVerified email at deakin.edu.au
Wanquan Liu,Curtin UniversityVerified email at curtin.edu.au

Santu Rana

Associate Professor of Computer Science, Deakin University

Verified email at deakin.edu.au - Homepage

Machine Learning Bayesian Optimization Robotics Adversarial Learning


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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	836	2016
Bayesian optimization for adaptive experimental design: A review S Greenhill, S Rana, S Gupta, P Vellanki, S Venkatesh IEEE access 8, 13937-13948, 2020	390	2020
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	128	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	127	2017
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), 5683, 2017	126	2017
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	125	2021
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	111	2016
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	96	2017
Differentially private random forest with high utility S Rana, SK Gupta, S Venkatesh 2015 IEEE international conference on data mining, 955-960, 2015	90	2015
Fast hyperparameter tuning using Bayesian optimization with directional derivatives TT Joy, S Rana, S Gupta, S Venkatesh Knowledge-Based Systems 205, 106247, 2020	71	2020
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	70	2019
Bayesian optimization for categorical and category-specific continuous inputs D Nguyen, S Gupta, S Rana, A Shilton, S Venkatesh Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5256-5263, 2020	67	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	61	2019
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	59	2014
Exploration enhanced expected improvement for Bayesian optimization J Berk, V Nguyen, S Gupta, S Rana, S Venkatesh Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019	56	2019
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	56*	2014
Batch Bayesian optimization using multi-scale search TT Joy, S Rana, S Gupta, S Venkatesh Knowledge-Based Systems 187, 104818, 2020	49	2020
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	48	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	42	2015
Regret bounds for transfer learning in Bayesian optimisation A Shilton, S Gupta, S Rana, S Venkatesh Artificial Intelligence and Statistics, 307-315, 2017	39	2017

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