Wide & Deep Learning for Recommender Systems
该文章也是RS很经典的一篇论文，由Google发表，应用于Play Store的Wide&Deep模型。 推荐系统，与搜索排序问题类似，一个挑战是同时实现 记忆 memorization 和 泛化 generalization Memorization 记忆，可以大致定义为：学习物品或特征的频繁共现，并利用历史数据中的相关性 利用稀疏特征上的 叉乘变换 cross-product transfor
相关文章
- 1. Wide & Deep Learning for Recommender Systems
- 2. Wide &Deep Learning for Recommender Systems
- 3. Wide & Deep Learning for Recommender Systems论文笔记
- 4. 《Wide & Deep Learning for Recommender Systems》论文总结
- 5. 论文笔记 - Wide & Deep Learning for Recommender Systems
- 6. #Paper Reading# Wide & Deep Learning for Recommender Systems
- 7. 论文阅读：《Wide & Deep Learning for Recommender Systems》
- 8. Wide & Deep Learning for Recommender Systems 翻译
- 9. 论文笔记：Wide & Deep Learning for Recommender Systems
- 10. Wide & Deep Learning for Recommender Systems 模型实践
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相关文章
- 1. Wide & Deep Learning for Recommender Systems
- 2. Wide &Deep Learning for Recommender Systems
- 3. Wide & Deep Learning for Recommender Systems论文笔记
- 4. 《Wide & Deep Learning for Recommender Systems》论文总结
- 5. 论文笔记 - Wide & Deep Learning for Recommender Systems
- 6. #Paper Reading# Wide & Deep Learning for Recommender Systems
- 7. 论文阅读：《Wide & Deep Learning for Recommender Systems》
- 8. Wide & Deep Learning for Recommender Systems 翻译
- 9. 论文笔记：Wide & Deep Learning for Recommender Systems
- 10. Wide & Deep Learning for Recommender Systems 模型实践