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lstm

2 notes, newest first.

  1. ADORN: Adaptive Drift handling for Open RAN using Reinforcement Learning

    Source note ·

    The paper proposes a Q-learning based adaptive retraining approach for Open Radio Access Networks (O-RAN) using Reinforcement Learning (RL). The goal is to balance forecasting accuracy and retraining cost, which can…

  2. ADORN: Adaptive Drift handling for Open RAN using Reinforcement Learning

    Source note ·

    Researchers propose a Q-learning-based adaptive retraining approach using Reinforcement Learning (RL) to handle drift in Open Radio Access Networks (O-RAN). This approach aims to balance forecasting accuracy and…