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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