Training is carried out by Stochastic Gradient Descent (SGD), updating W and r at each step, following Bordes et al., 2013).
at the start of training the parameters to be learnt (the n v × k word/feature embeddings in W and the n r × k relation embeddings r ) are initialized to random weights.