mathematical and conceptual properties of the softmax function. It also provides two mathematical derivations (as a stochastic choice model, and as maximum en-tropy distribution), together …

Softmax is usually used for multi-category classification as the last layer in neural networks like ResNet or MobileNet. It is also used as an activation layer in intermediate layers in some …

Softmax satisfies the axioms of probability Axiom #1, probabilities are non-negative ( 0 ≥ 0). There are many ways to do this, but one way that works is to choose: ∝ exp Axiom #2, probabilities …

The softmax function is an indispensable component of multiclass classifiers ranging from multinomial logistic re-gression models to deep neural networks (NNs).

Softmax function is often used to highlight the largest values and suppress values which are significantly below the maximum value.

Another important representation of the softmax function can be derived by considering the “argmax function” under entropy regularization.2 Let z 2 Rn, and consider the argmax of x>z …

A natural question is: why is softmax so effective? In this paper, we provide a possible explanation for this effectiveness: namely, we prove that softmax is the only consistent approach to …