Pears, R. L. (2022). Utilizing Noise as an Attack Independent Measure for Representing Privacy in Logistic Cumulative Noise Addition.
Pears, R. (2021). Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information. Yes, this was part of Ben Halstead's PhD research whom I supervised when I was in New Zealand. 2021 IEEE 37th International Conference on Data Engineering (ICDE). https://ieeexplore.ieee.org/abstract/document/9458895
Pears, R. (2022). Novel method for optimizing performance in resource constrained distributed data streams. Yes, this is a paper that is part of Rashi Bhalla PhD research. Rashi is a former PhD student of mine.. 1-19. New York: Springer. https://doi.org/10.1007/s10489-021-03019-5
Pears, R. (2021). Analyzing and repairing concept drift adaptation in data stream classification. Yes, part of Ben Halstead's PhD research which I supervised along with members of staff at the University of Auckland, New Zealand. 1-35. Springer. https://link.springer.com/article/10.1007/s10994-021-05993-w
Pears, R. (2021). Recurring concept memory management in data streams: exploiting data stream concept evolution to improve performance and transparency. 35, 796-836. SpringerLink. https://link.springer.com/article/10.1007/s10618-021-00736-w
Pears, R. (2021). Topical affinity in short text microblogs. Yes, this was part of Herman Wandabwa's work whom I supervised when I was at the Auckland University of Technology in New Zealand. Wiley.
Pears, R. L. Multi-interest semantic changes over time in short-text microblogs. 228(27), . Elsevier. https://doi.org/10.1016/j.knosys.2021.107249
