Decision tree classification with differential privacy: A survey S Fletcher, MZ Islam ACM Computing Surveys (CSUR) 52 (4), 1-33, 2019 | 126 | 2019 |
Comparing sets of patterns with the Jaccard index S Fletcher, MZ Islam Australasian Journal of Information Systems 22, 2018 | 115 | 2018 |
Differentially private random decision forests using smooth sensitivity S Fletcher, MZ Islam Expert systems with applications 78, 16-31, 2017 | 92 | 2017 |
A Differentially Private Decision Forest. S Fletcher, MZ Islam AusDM 15, 99-108, 2015 | 51 | 2015 |
Measuring information quality for privacy preserving data mining S Fletcher, MZ Islam International Journal of Computer Theory and Engineering 7 (1), 21-28, 2015 | 39 | 2015 |
A differentially private random decision forest using reliable signal-to-noise ratios S Fletcher, MZ Islam AI 2015: Advances in Artificial Intelligence: 28th Australasian Joint …, 2015 | 26 | 2015 |
Optimizing clustering to promote data diversity when generating an ensemble classifier ZM Jan, B Verma, S Fletcher Proceedings of the genetic and evolutionary computation conference companion …, 2018 | 14 | 2018 |
Removing bias from diverse data clusters for ensemble classification S Fletcher, B Verma Neural Information Processing: 24th International Conference, ICONIP 2017 …, 2017 | 14 | 2017 |
An anonymization technique using intersected decision trees S Fletcher, MZ Islam Journal of King Saud University-Computer and Information Sciences 27 (3 …, 2015 | 14 | 2015 |
Quality evaluation of an anonymized dataset S Fletcher, MZ Islam 2014 22nd International Conference on Pattern Recognition, 3594-3599, 2014 | 13 | 2014 |
A non-specialized ensemble classifier using multi-objective optimization S Fletcher, B Verma, M Zhang Neurocomputing 409, 93-102, 2020 | 12 | 2020 |
The optimized selection of base-classifiers for ensemble classification using a multi-objective genetic algorithm S Fletcher, B Verma, ZM Jan, M Zhang 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 12 | 2018 |
Measuring rule retention in anonymized data–when one measure is not enough S Fletcher, MZ Islam Transactions On Data Privacy 10 (3), 175-201, 2017 | 6 | 2017 |
Towards protecting sensitive text with differential privacy S Fletcher, A Roegiest, AK Hudek 2021 IEEE 20th International Conference on Trust, Security and Privacy in …, 2021 | 3 | 2021 |
Pruning high-similarity clusters to optimize data diversity when building ensemble classifiers S Fletcher, B Verma International Journal of Computational Intelligence and Applications 18 (04 …, 2019 | 3 | 2019 |
Data mining and privacy: Modeling sensitive data with differential privacy S Fletcher Charles Sturt University, 2017 | 1 | 2017 |
Measuring pattern retention in anonymized data--where one measure is not enough S Fletcher, MZ Islam arXiv preprint arXiv:1512.07721, 2015 | 1 | 2015 |
Hash the Universe: Differentially Private Text Extraction with Feature Hashing S Fletcher, A Roegiest, AK Hudek | | 2022 |
Measuring the Similarity between Rule Lists S Fletcher, MZ Islam The 14th Australasian Data Mining Conference: AusDM 2016, 1-8, 2016 | | 2016 |