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schludy t1_j7v9pkm wrote

Reply to comment by zanzagaes2 in [P] Creating an embedding from a CNN by zanzagaes2

I think you're underestimating the curse of dimensionality. In 500d, most vectors will be far away from each other. You can't just use L2 norm when comparing the vectors in that high dimensional space

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zanzagaes2 OP t1_j7vpd89 wrote

Yes, I think that's the case because I am getting far more reasonable values comparing the projection to 2d/3d of the embedding rather than the full 500 feature vector.

Is there a better way to do this than projecting into a smaller space (using reduction dimensionality techniques or encoder-decoder approach) and using L2 there?

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