Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression

Kabir, Shaily; Wagner, Christian; Ellerby, Zack

doi:10.1109/tai.2023.3234930

All Outputs (4)

A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic (2023)
Journal Article
Hasan, M. M., Jahan, M., & Kabir, S. (2023). A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic. IEEE Transactions on Intelligent Transportation Systems, 1-14. https://doi.org/10.1109/tits.2023.3305342

Trust establishment among vehicles is essential for vehicular ad hoc networks (VANETs) as it directly impacts the security and privacy of vehicular communication. Many trust estimation approaches have been introduced, however, they often suffer from... Read More about A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic.

A Restricted Parametrized Model for Interval-Valued Regression (2023)
Conference Proceeding
Ying, J., Kabir, S., & Wagner, C. (2023). A Restricted Parametrized Model for Interval-Valued Regression. . https://doi.org/10.1109/fuzz52849.2023.10309686

This paper explores the parameter generation of the existing ‘Parametrized Model’ (PM) as the state-of-the-art linear interval-valued regression model, highlighting that its strong performance may arise from unexpected behavior. Focusing on the appro... Read More about A Restricted Parametrized Model for Interval-Valued Regression.

An end-to-end authentication mechanism for Wireless Body Area Networks (2023)
Journal Article
Jahan, M., Zohra, F. T., Parvez, M. K., Kabir, U., Al Radi, A. M., & Kabir, S. (2023). An end-to-end authentication mechanism for Wireless Body Area Networks. Smart Health, 29, Article 100413. https://doi.org/10.1016/j.smhl.2023.100413

Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression (2023)
Journal Article
Kabir, S., Wagner, C., & Ellerby, Z. (2023). Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression. IEEE Transactions on Artificial Intelligence, 1-19. https://doi.org/10.1109/tai.2023.3234930

Most of statistics and AI draw insights through modelling discord or variance between sources (i.e., inter-source) of information. Increasingly however, research is focusing on uncertainty arising at the level of individual measurements (i.e., within... Read More about Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression.