Hong Gunn Chew

17 papers B 1Misc 6Journal 6Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Algebraic Adversarial Attacks on Explainability Models.
CoRR
Lachlan Simpson, Federico Costanza, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
2025 — conf
Graph-Based Integrated Gradients for Explaining Graph Neural Networks.
AI (1)
Lachlan Simpson, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
2025 J jnl
Graph-based Integrated Gradients for Explaining Graph Neural Networks.
CoRR
Lachlan Simpson, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
2025 — conf
Probabilistic Lipschitzness and the Stable Rank for Measuring XAI Model Robustness.
AI (1)
Lachlan Simpson, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
2025 J jnl
Tangentially Aligned Integrated Gradients for User-Friendly Explanations.
CoRR
Lachlan Simpson, Federico Costanza, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
2024 Misc conf
Algebraic Adversarial Attacks on Integrated Gradients.
ICMLC
Lachlan Simpson, Federico Costanza, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
2024 J jnl
Algebraic Adversarial Attacks on Integrated Gradients.
CoRR
Lachlan Simpson, Federico Costanza, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
2024 J jnl
Probabilistic Lipschitzness and the Stable Rank for Comparing Explanation Models.
CoRR
Lachlan Simpson, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
2024 — conf
Tangentially Aligned Integrated Gradients for User-Friendly Explanations.
AICS
Lachlan Simpson, Federico Costanza, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
2023 Misc conf
A Testbed for Automating and Analysing Mobile Devices and Their Applications.
ICMLC
Lachlan Simpson, Kyle Millar, Adriel Cheng, Hong Gunn Chew, Cheng-Chew Lim
2023 J jnl
A Testbed for Automating and Analysing Mobile Devices and their Applications.
CoRR
Lachlan Simpson, Kyle Millar, Adriel Cheng, Hong Gunn Chew, Cheng-Chew Lim
2021 Misc conf
Clustering Network-Connected Devices Using Affiliation Graphs.
ICMLC
Kyle Millar, Adriel Cheng, Hong Gunn Chew, Cheng-Chew Lim
2021 Misc conf
Detecting Botnet Victims Through Graph-Based Machine Learning.
ICMLC
Kyle Millar, Lachlan Simpson, Adriel Cheng, Hong Gunn Chew, Cheng-Chew Lim
2020 B conf
Characterising Network-Connected Devices Using Affiliation Graphs.
NOMS
Kyle Millar, Adriel Cheng, Hong Gunn Chew, Cheng-Chew Lim
2020 Misc conf
Operating System Classification: A Minimalist Approach.
ICMLC
Kyle Millar, Adriel Cheng, Hong Gunn Chew, Cheng-Chew Lim
2018 — conf
Deep Learning for Classifying Malicious Network Traffic.
PAKDD (Workshops)
Kyle Millar, Adriel Cheng, Hong Gunn Chew, Cheng-Chew Lim
2001 Misc conf
Dual ν-support vector machine with error rate and training size biasing.
ICASSP
Hong Gunn Chew, Robert E. Bogner, Cheng-Chew Lim