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Information Theory

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Core Concepts

  • Information content
  • Entropy
  • Joint entropy
  • Conditional entropy
  • Mutual information
  • Cross-entropy
  • KL divergence (Kullback-Leibler Divergence)

Applications in Large Models

Loss Function

  • Cross-entropy loss is a measure of the difference between the predicted distribution and the true distribution.

Attention Mechanism

  • When computing attention weights, the softmax operation relates to probability distributions and entropy.

Reinforcement Learning

  • The optimization objective in policy gradient may include an entropy regularization term to encourage exploration.
  • The core of TRPO / PPO algorithms is a KL divergence constraint.

Model Compression and Quantization

  • Evaluating quantization information loss.

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