8 citations · 13 across the 7 of their papers we have counts for
4 papers · 1 filter
TSI-GAN: Unsupervised Time Series Anomaly Detection using Convolutional Cycle-Consistent Generative Adversarial Networks
Shyam Sundar Saravanan, Tie Luo, Mao Van Ngo
Anomaly detection is widely used in network intrusion detection, autonomous driving, medical diagnosis, credit card frauds, etc. However, several key challenges remain open, such a…
Adaptive Anomaly Detection for Internet of Things in Hierarchical Edge Computing: A Contextual-Bandit Approach
Mao V. Ngo, Tie Luo, Tony Q. S. Quek
The advances in deep neural networks (DNN) have significantly enhanced real-time detection of anomalous data in IoT applications. However, the complexity-accuracy-delay dilemma per…
Contextual-Bandit Anomaly Detection for IoT Data in Distributed Hierarchical Edge Computing
Mao V. Ngo, Tie Luo, Hakima Chaouchi +1
Advances in deep neural networks (DNN) greatly bolster real-time detection of anomalous IoT data. However, IoT devices can hardly afford complex DNN models, and offloading anomaly…
Adaptive Anomaly Detection for IoT Data in Hierarchical Edge Computing
Mao V. Ngo, Hakima Chaouchi, Tie Luo +1
Advances in deep neural networks (DNN) greatly bolster real-time detection of anomalous IoT data. However, IoT devices can barely afford complex DNN models due to limited computati…