Similarly,thetexture ofacloth mayconfuse classifying clothing categories (shirts vs. skirts), but it is crucial for classifying fashion attributes (spottedvs.

Using the method of auxiliary coordinates, we derive a training algorithm that works by alternating steps that train an auxiliary embeddingwith steps that train the mapping.

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We thank all reviewers for their valuable comments. Below, we first address the common concerns and then answer the detailed questions. It leads to smaller bias (see Fig. A), which also agrees with Thm. 2. First, introducing latent variables can improve the sample quality (w.r.t. Indeed, we update Tab. 2 and obtain Tab. As stated in L290, a similar protocol is adopted in MDSM [34].