Abigail M. Y. Koay

21 papers A* 1A 1B 1Misc 2Journal 8Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
Multi-agent reinforcement curriculum learning for real unmanned ground vehicles.
Eng. Appl. Artif. Intell.
Timothy Mead, Zhe Wang, Ernest Foo, Jinsong Dong, Naipeng Dong, Ryan Kok Leong Ko, Abigail M. Y. Koay, Kien Nguyen Thanh, Yue Xu, Junae Kim, Stephen Bornstein, Zhe Hou
2025 J jnl
Adapting to the stream: an instance-attention GNN method for irregular multivariate time series data.
Frontiers Comput. Sci.
Kun Han, Abigail M. Y. Koay, Ryan K. L. Ko, Weitong Chen, Miao Xu
2025 B conf
HITS: Hierarchical Interpretable Time Series Classification via Multiple Instance Learning.
IJCNN
Kun Han, Abigail M. Y. Koay
2024 J jnl
AI hype as a cyber security risk: the moral responsibility of implementing generative AI in business.
AI Ethics
Declan Humphreys, Abigail M. Y. Koay, Dennis Desmond, Erica Mealy
2024 Misc conf
Mining Irregular Time Series Data with Noisy Labels: A Risk Estimation Approach.
ADC
Kun Han, Abigail M. Y. Koay, Ryan K. L. Ko, Weitong Chen, Miao Xu
2023 J jnl
Machine learning in industrial control system (ICS) security: current landscape, opportunities and challenges.
J. Intell. Inf. Syst.
Abigail M. Y. Koay, Ryan K. L. Ko, Hinne Hettema, Kenneth Radke
2022 J jnl
Benchmarking and learning garbage collection delays for resource-restricted graphical user interfaces.
Softw. Pract. Exp.
Harry McCarthy, Abigail M. Y. Koay, Michael Dawson, Kenneth B. Kent, Panos Patros
2022 — conf
Domain Generalisation for Glaucoma Detection in Retinal Images from Unseen Fundus Cameras.
ACIIDS (2)
Hansi Gunasinghe, James McKelvie, Abigail M. Y. Koay, Michael Mayo
2022 A* conf
Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization.
NeurIPS
Jonathan Wilton, Abigail M. Y. Koay, Ryan K. L. Ko, Miao Xu, Nan Ye
2022 J jnl
Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization.
CoRR
Jonathan Wilton, Abigail M. Y. Koay, Ryan K. L. Ko, Miao Xu, Nan Ye
2021 — conf
Comparison Of Pretrained Feature Extractors For Glaucoma Detection.
ISBI
Hansi Gunasinghe, James McKelvie, Abigail M. Y. Koay, Michael Mayo
2021 — conf
Plan2Defend: AI Planning for Cybersecurity in Smart Grids.
ISGT Asia
Taejun Choi, Ryan K. L. Ko, Tapan Kumar Saha, Joshua D. Scarsbrook, Abigail M. Y. Koay, Shunyao Wang, Wenlu Zhang, Connor St Clair
2021 — conf
SDGen: A Scalable, Reproducible and Flexible Approach to Generate Real World Cyber Security Datasets.
UbiSec
Abigail M. Y. Koay, Miao Xie, Ryan K. L. Ko, Charles Sterner, Taejun Choi, Naipeng Dong
2020 A conf
Embedding Java Classes with code2vec: Improvements from Variable Obfuscation.
MSR
Rhys Compton, Eibe Frank, Panos Patros, Abigail M. Y. Koay
2020 J jnl
Embedding Java Classes with code2vec: Improvements from Variable Obfuscation.
CoRR
Rhys Compton, Eibe Frank, Panos Patros, Abigail M. Y. Koay
2020 — conf
In Silico Comparison of Continuous Glucose Monitor Failure Mode Strategies for an Artificial Pancreas.
KDH@ECAI
Yunjie Lisa Lu, Abigail M. Y. Koay, Michael Mayo
2019 Misc conf
(Short Paper) Effectiveness of Entropy-Based Features in High- and Low-Intensity DDoS Attacks Detection.
IWSEC
Abigail M. Y. Koay, Ian Welch, Winston K. G. Seah
2019 — —
Detecting High and Low Intensity Distributed Denial of Service (DDoS) Attacks.
Abigail M. Y. Koay
2019 — conf
Maintaining SLOs of Cloud-Native Applications Via Self-Adaptive Resource Sharing.
SASO
Vladimir Podolskiy, Michael Mayo, Abigail M. Y. Koay, Michael Gerndt, Panos Patros
2018 — conf
A new multi classifier system using entropy-based features in DDoS attack detection.
ICOIN
Abigail M. Y. Koay, Aaron Chen, Ian Welch, Winston K. G. Seah
2018 J jnl
Fog-Assisted SDN Controlled Framework for Enduring Anomaly Detection in an IoT Network.
IEEE Access
Qaisar B. Shafi, Abdul Basit, Saad B. Qaisar, Abigail M. Y. Koay, Ian Welch