  We show the equivalence of two state-of-the-art link prediction/knowledge
graph completion methods: Nickel et al's holographic embedding and Trouillon et
al.'s complex embedding. We first consider a spectral version of the
holographic embedding, exploiting the frequency domain in the Fourier transform
for efficient computation. The analysis of the resulting method reveals that it
can be viewed as an instance of the complex embedding with certain constraints
cast on the initial vectors upon training. Conversely, any complex embedding
can be converted to an equivalent holographic embedding.
