In other words, if we take a matrix from F (A) and apply the softmax function to each of its rows, we obtain a matrix that consists of true probability distributions.
for some A ∈ F (A), training RNN language models is to find the parameters satisfying the following equation: Equation 6 indicates that training RNN language models can also be interpreted as a matrix factorization problem.