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cs.LG2024
State Frequency Estimation for Anomaly Detection
Clinton Cao, Agathe Blaise, Annibale Panichella +1
Many works have studied the efficacy of state machines for detecting anomalies within NetFlows. These works typically learn a model from unlabeled data and compute anomaly scores f…
cs.LG2024★ 1 cited
Optimizing Interpretable Decision Tree Policies for Reinforcement Learning
Daniël Vos, Sicco Verwer
Reinforcement learning techniques leveraging deep learning have made tremendous progress in recent years. However, the complexity of neural networks prevents practitioners from und…