KL divergence

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想请教各位大侠 KL divergence的问题，wiki上说 KL measures the expected number of extra bits required to code samples from P when using a code based on Q, rather than using a code based on P. Typically P represents the "true" distribution of data, observations, or a precisely calculated theoretical distribution. The measure Q typically represents a theory, model, description, or approximation of P.

公式是

通常P是unknown的，Q是一个对P的approximation， 也就是说Q的概率是可求出来的，但是对于unknown的P，如何求出相对熵呢？也就是说这里p(x)是怎么得到的呢？


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关键词：DIVERGENCE div NCE Ver distribution represents precisely expected measures required