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https://arxiv.org/pdf/1906.00091.pdf
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Facebookが開発したopen sourceのDeepな推薦モデル(MIT Licence)。
モデル自体はシンプルで、continuousなfeatureをMLPで線形変換、categoricalなfeatureはembeddingをlook upし、それぞれfeatureのrepresentationを獲得。 その上で、それらをFactorization Machines layer(second-order)にぶちこむ。すなわち、Feature間の2次の交互作用をembedding間のdot productで獲得し、これを1次項のrepresentationとconcatしMLPにぶちこむ。最後にシグモイド噛ませてCTRの予測値とする。
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実装: https://github.com/facebookresearch/dlrm
Parallelism以後のセクションはあとで読む
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https://arxiv.org/pdf/1906.00091.pdf
The text was updated successfully, but these errors were encountered: