| Enhancing random projection with independent and cumulative additive noise for privacy-preserving data stream mining B Denham, R Pears, MA Naeem Expert Systems with Applications 152, 113380, 2020 | 29 | 2020 |
| HDSM: A distributed data mining approach to classifying vertically distributed data streams B Denham, R Pears, MA Naeem Knowledge-Based Systems 189, 105114, 2020 | 10 | 2020 |
| Gain-Some-Lose-Some: Reliable Quantification Under General Dataset Shift B Denham, EMK Lai, R Sinha, MA Naeem 2021 IEEE International Conference on Data Mining (ICDM), 1048-1053, 2021 | 9 | 2021 |
| Null-Labelling: A Generic Approach for Learning in the Presence of Class Noise B Denham, R Pears, MA Naeem 2020 IEEE International Conference on Data Mining (ICDM), 990-995, 2020 | 4 | 2020 |
| Evaluating the quality of Drupal software modules B Denham, R Pears, AM Connor International Journal of Software Engineering and Knowledge Engineering 28 …, 2018 | 4 | 2018 |
| Witan: unsupervised labelling function generation for assisted data programming B Denham, EMK Lai, R Sinha, MA Naeem Proceedings of the VLDB Endowment 15 (11), 2334-2347, 2022 | 2 | 2022 |
| Novel methods for distributed and privacy-preserving data stream mining BJ Denham Auckland University of Technology, 2019 | 1 | 2019 |
| Dynamic Quantification with Constrained Error Under Unknown General Dataset Shift B Denham, EMK Lai, R Sinha, MA Naeem IEEE Transactions on Knowledge and Data Engineering, 2024 | | 2024 |
| Tolerant Machine Learning for Deficient Training Data BJ Denham Auckland University of Technology, 2023 | | 2023 |
