Xiao et al., 2017 - Google Patents

Attentional factorization machines: Learning the weight of feature interactions via attention networks

Xiao et al., 2017

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Document ID
12533939833044531139
Author
Xiao J
Ye H
He X
Zhang H
Wu F
Chua T
Publication year
Publication venue
arXiv preprint arXiv:1708.04617

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Snippet

Factorization Machines (FMs) are a supervised learning approach that enhances the linear regression model by incorporating the second-order feature interactions. Despite effectiveness, FM can be hindered by its modelling of all feature interactions with the same …
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    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
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