AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Reinforcement-learning policies for robot locomotion can fail at deployment when operating conditions shift (e.g., rough or slippery terrain, payload changes, sensing degradation), and retraining or manual recalibration is often infeasible under on-device latency and memory constraints. We study test-time adaptation (T...
In a simulator for COVID19, even at epsilon=1 per message, this work can significantly improve the detection of potentially infected individuals and, as a result of targeted testing, reduce infection rates.
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