HMLET (Hybrid-Method-of-Linear-and-non-linEar-collaborative-filTering-method)

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Deep Learning HMLET
Overview

Methods

  • HMLET (Hybrid-Method-of-Linear-and-non-linEar-collaborative-filTering-method)

    • Dynamically selecting the best propagation method for each node in a layer using gating networks.

  • Four variants of HMLET: HMLET (End), HMLET (Middle), HMLET (Front), HMLET (All)

    • Four variants of HMLET in terms of the location of the non-linear propagation.

  • HMLET (End)

    • HMLET (End) shows best performance among these variants
    • Focusing on gating in the third and fourth layers
    • The detailed workflow of HMLET (End)

How to use

python main.py --dataset gowalla --model HMLET_End
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Comments
  • About the Gumbel-softmax

    About the Gumbel-softmax

    Hi author, thanks for your work!

    I want to ask you about the idea of the article, that is, why you should use Gumbel-softmax - if I understand correctly, the input in this article is not sampling.Even with softmax, there should be no differentiable problems without reparameterization.

    From the perspective of solving argmax‘s problem, I think softmax with temperature τ should also achieve a similar effect.

    My understanding is that according to the statement in Alg1 and 2, a one-hot control variable needs to be output, but the specific explanation is still vague.

    Best wishes！

    opened by ithok 1
Owner
Yong
Yong
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