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 | 746 | 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 | 319 | 2020 |
High dimensional Bayesian optimization using dropout C Li, S Gupta, S Rana, V Nguyen, S Venkatesh, A Shilton arXiv preprint arXiv:1802.05400, 2018 | 147 | 2018 |
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 | 120 | 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 | 118 | 2017 |
Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry S Gupta, T Tran, W Luo, D Phung, RL Kennedy, A Broad, D Campbell, ... BMJ open 4 (3), e004007, 2014 | 114 | 2014 |
Stable feature selection for clinical prediction: Exploiting ICD tree structure using Tree-Lasso I Kamkar, SK Gupta, D Phung, S Venkatesh Journal of biomedical informatics 53, 277-290, 2015 | 110 | 2015 |
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 | 103 | 2021 |
Nonnegative shared subspace learning and its application to social media retrieval SK Gupta, D Phung, B Adams, T Tran, S Venkatesh Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010 | 93 | 2010 |
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 | 92 | 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 | 89 | 2017 |
Differentially private random forest with high utility S Rana, SK Gupta, S Venkatesh 2015 IEEE International Conference on Data Mining, 955-960, 2015 | 84 | 2015 |
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 | 63 | 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 | 60 | 2020 |
SARS‐CoV‐2 infection and venous thromboembolism after surgery: an international prospective cohort study COVIDSurg Collaborative, GlobalSurg Collaborative, D Nepogodiev, ... Anaesthesia 77 (1), 28-39, 2022 | 59 | 2022 |
Phenomenology and beliefs of patients with Dhat syndrome: A nationwide multicentric study S Grover, A Avasthi, S Gupta, A Dan, R Neogi, PB Behere, B Lakdawala, ... International Journal of Social Psychiatry 62 (1), 57-66, 2016 | 58 | 2016 |
Regularized nonnegative shared subspace learning SK Gupta, D Phung, B Adams, S Venkatesh Data mining and knowledge discovery 26, 57-97, 2013 | 54 | 2013 |
Fast hyperparameter tuning using Bayesian optimization with directional derivatives TT Joy, S Rana, S Gupta, S Venkatesh Knowledge-Based Systems 205, 106247, 2020 | 53 | 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 | 53 | 2016 |
Proteomics unravel the regulating role of salicylic acid in soybean under yield limiting drought stress M Sharma, SK Gupta, B Majumder, VK Maurya, F Deeba, A Alam, ... Plant physiology and biochemistry 130, 529-541, 2018 | 52 | 2018 |