AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work proposes a framework for locally masked SAE-based anomaly detection, supported by theoretical justifications, and demonstrates their ability to capture meaningful safety information while using only 1-2% of SAE neurons for computation.
Time-Adaptive Robotic Control (TARC), a reinforcement learning framework in which the policy jointly predicts a control action and its duration of application, is introduced, and matches the performance of high-frequency discrete-time controllers while operating at less than half their control frequency.
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