論文閱讀：（AFM）Learning the Weight of Feature Interactions via Attention Networks
文章目錄 摘要 算法原理 1、基本原理 2、網絡結構 3、過擬合 摘要 AFM全稱是Attentional Factorization Machine，和NFM是同一個作者，NFM的解析可以參考這篇博客：https://blog.csdn.net/weixin_45459911/article/details/105702981 AFM是在FM上的改進，它最大的特點就是使用一個attention
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相關文章
- 1. 論文閱讀：ResNeSt: Split-Attention Networks
- 2. 論文閱讀：Deep Metric Learning via Lifted Structured Feature Embedding
- 3. 論文閱讀理解 - Deep Metric Learning via Lifted Structured Feature Embedding
- 4. 論文閱讀：Learning Human-Object Interactions by Graph Parsing Neural Networks
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- 9. [論文閱讀筆記] node2vec Scalable Feature Learning for Networks
- 10. 【論文閱讀】[meta learning]cross-domain few-shot classification via learned feature-wise transformation.