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Hi,i have run your source code,it seems that it works well,but i have one question,for the weights of the embeddings are inited randomly,and in tranning it always select the nearest neighbors,so is there any guarantee that not a few of embeddings always being selected?
The text was updated successfully, but these errors were encountered:
It's a good question. I do not have an answer though since I am not the authors of the paper.
In my humble opinion, describing in the conceptual level, embedding is also be trained to maximize interpretability of training examples, so it could become the most informative supports for a dataset.
Hi,i have run your source code,it seems that it works well,but i have one question,for the weights of the embeddings are inited randomly,and in tranning it always select the nearest neighbors,so is there any guarantee that not a few of embeddings always being selected?
The text was updated successfully, but these errors were encountered: