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: L S E ( x 1 , … , x n ) = log ( exp ( x 1 ) + ⋯ + exp ( x n ) ) .
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: L S E ( x 1 , … , x n ) = log ( exp ( x 1 ) + ⋯ + exp ( x n ) ) .
Source: Wikipedia "LogSumExp" · CC BY-SA 4.0
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