However, the fact is that, as long as W is orthogonal, optimizing the squared Euclidean distance of length-normalized embeddings is equivalent to optimizing the cosine, and therefore, the mapping objective proposed by Xing et al. (2015) is equivalent to that used by <cite>Mikolov et al. (2013b)</cite> with orthogonality constraint and unit vectors.