In information theory, h(x|y) represents the conditional entropy of random variable X given another random variable Y. It measures the amount of uncertainty remaining about X when Y is known, and connects directly to concepts like relative entropy and mutual information by providing insight into how knowing Y reduces uncertainty about X.
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