most citedFederated Learning for Anomaly Detection in Energy Consumption Data: Assessing the Vulnerability to Adversarial Attacks

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2 papers

cs.LG2025★ 1 cited

Federated Learning for Anomaly Detection in Energy Consumption Data: Assessing the Vulnerability to Adversarial Attacks

Yohannis Kifle Telila, Damitha Senevirathne, Dumindu Tissera +3

Anomaly detection is crucial in the energy sector to identify irregular patterns indicating equipment failures, energy theft, or other issues. Machine learning techniques for anoma…

cs.LG2018

Dynamic Planning Networks

Norman Tasfi, Miriam Capretz

We introduce Dynamic Planning Networks (DPN), a novel architecture for deep reinforcement learning, that combines model-based and model-free aspects for online planning. Our archit…