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Theory of Mixture-of-Experts for Mobile Edge Computing

  • Mobile edge computing (MEC) networks face the challenge of efficiently handling diverse machine learning tasks generated by mobile users.
  • The traditional approach of offloading tasks to the nearest available edge server can lead to overfitting or forgetting of previous tasks.
  • To address this, the mixture-of-experts (MoE) theory is introduced in MEC networks to improve continual learning (CL) performance.
  • An adaptive gating network is used to route tasks to specialized experts, reducing generalization error over time.

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