Closed sdeepaknarayanan closed 4 years ago
If we concat the embeddings, the representation space is enlarged. But if we sum up the embeddings, the representation space remains the same. That's what we mean by "more indicative of the embedding quality refined by GCN.". Hope it clarifies.
On Tue, Aug 25, 2020 at 12:47 PM Deepak Narayanan notifications@github.com wrote:
Hi, First off, very nice and interesting work 👍. In the paper, there's a claim that's made regarding the embedding concatenation v/s sum of all the embeddings.
e. Thus, we change the way of obtaining final embedding from concatenation (i.e., e ∗ u = e (0) u ∥· · · ∥e (L) u ) to
sum (i.e., e ∗ u = e (0) u + · · · + e (L) u ). Note that this change has little effect on NGCF’s performance, but makes the following ablation studies more indicative of the embedding quality refined by GCN.
Is there empirical evidence for this claim?
Thanks
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Hi @hexiangnan, Thanks for the quick response. I understood your point. However, my question was more along the lines of performance. Did you run experiments to compare concatenation with sum, because the paper seems to claim that this has little effect on the performance. I was hoping to see some experiments on the same.
As I remember, Deng Kuan (the second author) did the experiments. Concating does not degrade the performance, also does not improve.
On Tue, Aug 25, 2020 at 1:57 PM Deepak Narayanan notifications@github.com wrote:
Hi @hexiangnan, Thanks for the quick response. I understood your point. However, my question was more along the lines of performance. Did you run experiments to compare concatenation with sum, because the paper seems to claim that this has little effect on the performance. I was hoping to see some experiments on the same.
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Thanks for the response. :)
Hi, First off, very nice and interesting work 👍. In the paper, there's a claim that's made regarding the embedding concatenation v/s sum of all the embeddings.
Is there empirical evidence for this claim?
Thanks