11 citations · 12 across the 3 of their papers we have counts for
4 papers · 1 filter
Enhancing Robustness of On-line Learning Models on Highly Noisy Data
Zilong Zhao, Robert Birke, Rui Han +4
Classification algorithms have been widely adopted to detect anomalies for various systems, e.g., IoT, cloud and face recognition, under the common assumption that the data source…
Event-Based Control for Online Training of Neural Networks
Zilong Zhao, Sophie Cerf, Bogdan Robu +1
Convolutional Neural Network (CNN) has become the most used method for image classification tasks. During its training the learning rate and the gradient are two key factors to tun…
Feedback Control for Online Training of Neural Networks
Zilong Zhao, Sophie Cerf, Bogdan Robu +1
Convolutional neural networks (CNNs) are commonly used for image classification tasks, raising the challenge of their application on data flows. During their training, adaptation i…
RAD: On-line Anomaly Detection for Highly Unreliable Data
Zilong Zhao, Robert Birke, Rui Han +4
Classification algorithms have been widely adopted to detect anomalies for various systems, e.g., IoT, cloud and face recognition, under the common assumption that the data source…