Supplementary Material for the Paper " Sampling-Decomposable Generative Adversarial Recommender "

In the appendix, we start from the proofs of theorem 2.1 and theorem 2.2 in section A. Then, we prove the correctness of proposition 2.2 and proposition 2.3 in section B. After that, the detailed derivation of our proposed loss is provided in section C. At last, the sensitivity of some important Before providing the proofs of the theorems, we restate some important notations first. Here, we also restate some important notations first. Here, we illustrate the detailed derivation of our approximated loss for learning the discriminator. Figure 1(a) demonstrates the effects of the embeddings size (i.e., Figure 1(b) shows the effects of the number of item sample set for learning the discriminator. Figure 1(c) reports the effects of the number of item and context sample set for learning the generator.