Huy Tu

Tu, H., Yu, Z., & Menzies, T. (2022). Better Data Labelling With EMBLEM (and how that Impacts Defect Prediction). IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 48(1), 278–294. https://doi.org/10.1109/TSE.2020.2986415

Tu, H., & Menzies, T. (2022). DebtFree: minimizing labeling cost in self-admitted technical debt identification using semi-supervised learning. EMPIRICAL SOFTWARE ENGINEERING, 27(4). https://doi.org/10.1007/s10664-022-10121-w

Chakraborty, J., Majumder, S., & Tu, H. (2022). Fair-SSL: Building fair ML Software with less data. 2022 IEEE/ACM INTERNATIONAL WORKSHOP ON EQUITABLE DATA & TECHNOLOGY (FAIRWARE 2022), pp. 1–8. https://doi.org/10.1145/3524491.3527305

Yu, Z., Fahid, F. M., Tu, H., & Menzies, T. (2022). Identifying Self-Admitted Technical Debts With Jitterbug: A Two-Step Approach. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 48(5), 1676–1691. https://doi.org/10.1109/TSE.2020.3031401

Tu, H., & Menzies, T. (2021). FRUGAL: Unlocking Semi-Supervised Learning for Software Analytics. 2021 36TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING ASE 2021, pp. 394–406. https://doi.org/10.1109/ASE51524.2021.9678617

Tu, H., Papadimitriou, G., Kiran, M., Wang, C., Mandal, A., Deelman, E., & Menzies, T. (2021). Mining Workflows for Anomalous Data Transfers. 2021 IEEE/ACM 18TH INTERNATIONAL CONFERENCE ON MINING SOFTWARE REPOSITORIES (MSR 2021), pp. 1–12. https://doi.org/10.1109/MSR52588.2021.00013

Tu, H., & Nair, V. (2018). Is One Hyperparameter Optimizer Enough? PROCEEDINGS OF THE 4TH ACM SIGSOFT INTERNATIONAL WORKSHOP ON SOFTWARE ANALYTICS (SWAN'18), pp. 19–25. https://doi.org/10.1145/3278142.3278145