If For all the methods, we create 100 mini-batches on each dataset, and conduct a grid search to find hyperparameters that maximize MRR on the validation set, with at most 1000 iterations over the training set.
we tune the embedding size d ∈ {100, 150, 200}, the L 2 regularization coefficient η ∈ {0.001, 0.003, 0.01, 0.03, 0.1}, the ratio of negative over positive training examples α ∈ {2, 10}, and the initial learning rate γ ∈ {0.01, 0.05, 0.1, 0.5, 1.0}.