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Comparative Graph-based Summarization of Scientific Papers Guided by Comparative Citations
And then, we propose the comparative graph-based summarization (CGSUM) method to create comparative summaries using citations as guidance.
Comparative Study on Semi-supervised Learning Applied for Anomaly Detection in Hydraulic Condition Monitoring System
This study systematically compares semi-supervised learning methods applied for anomaly detection in hydraulic condition monitoring systems.
Learning from Symmetry: Meta-Reinforcement Learning with Symmetrical Behaviors and Language Instructions
We propose a dual-MDP meta-reinforcement learning method that enables learning new tasks efficiently with symmetrical behaviors and language instructions.
Comparative Study on Supervised versus Semi-supervised Machine Learning for Anomaly Detection of In-vehicle CAN Network
To enhance the security of in-vehicle networks and promote the research in this area, based upon a large scale of CAN network traffic data with the extracted valuable features, this study comprehensively compared fully-supervised machine learning with semi-supervised machine learning methods for CAN message anomaly detection.
