Translations:Softmax Function/34/en: Difference between revisions

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    * '''Attention mechanisms''': Softmax normalizes alignment scores into attention weights in the [[Attention Mechanisms|Transformer]] architecture.
    * '''{{Term|attention}} mechanisms''': Softmax normalizes alignment scores into {{Term|attention}} weights in the [[Attention Mechanisms|Transformer]] architecture.
    * '''Reinforcement learning''': Softmax over action-value estimates produces a stochastic policy (Boltzmann exploration).
    * '''Reinforcement learning''': Softmax over action-value estimates produces a stochastic policy (Boltzmann exploration).
    * '''Mixture models''': Softmax parameterizes mixing coefficients in mixture-of-experts architectures.
    * '''Mixture models''': Softmax parameterizes mixing coefficients in {{Term|mixture of experts|mixture-of-experts}} architectures.

    Latest revision as of 23:34, 27 April 2026

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    Message definition (Softmax Function)
    * '''{{Term|attention}} mechanisms''': Softmax normalizes alignment scores into {{Term|attention}} weights in the [[Attention Mechanisms|Transformer]] architecture.
    * '''Reinforcement learning''': Softmax over action-value estimates produces a stochastic policy (Boltzmann exploration).
    * '''Mixture models''': Softmax parameterizes mixing coefficients in {{Term|mixture of experts|mixture-of-experts}} architectures.
    • attention mechanisms: Softmax normalizes alignment scores into attention weights in the Transformer architecture.
    • Reinforcement learning: Softmax over action-value estimates produces a stochastic policy (Boltzmann exploration).
    • Mixture models: Softmax parameterizes mixing coefficients in mixture-of-experts architectures.
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