Lesson plan
LogSumExp
The LogSumExp (LSE) (also called RealSoftMax or multivariable softplus) function is a smooth maximum – a smooth approximation to the maximum function, mainly used by machine learning algorithms. It is defined as the logarithm of the sum of the exponentials of the arguments: \mathrm{LSE}(x_1, \dots, x_n) = \log\left( \exp(x_1) + \cdots + \exp(x_n) \right).
Article summary
The LogSumExp (LSE) (also called RealSoftMax or multivariable softplus) function is a smooth maximum – a smooth approximation to the maximum function, mainly used by machine learning algorithms. It is defined as the logarithm of the sum of the exponentials of the arguments: \mathrm{LSE}(x_1, \dots, x_n) = \log\left( \exp(x_1) + \cdots + \exp(x_n) \right).
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