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Support for Bayesian Personalized Ranking #46

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jerry-rubikloud opened this issue Feb 16, 2019 · 1 comment

jerry-rubikloud commented Feb 16, 2019

Hi there, I'm thinking of contributing codes for BPR. What is the best way to extend the code to handle this optimization in your opinion?

Owner

geffy commented Feb 17, 2019 •

edited

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Hi @jerry-rubikloud !
I think that we need to implement 2 components:

BPRSampler. It will generate pairs from source data and put them into batch. Example: for N pairs we will have a batch with N*2 samples (2 * i-th are winners, 2 * i + 1-th are losers)
BRPLoss. It will take expanded batch output ([2*N, 1]), convert it to pairs ([N, 2]) and calculate resulting loss.
This design seems to be easy for implementation and allows to keep FM core routine unchanged

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