论文笔记：Wide & Deep Learning for Recommender Systems
论文提要 本文在推荐方面提出一种wide & deep learning算法，也就是将一个宽的线性模型和一个深度神经网络一起训练，通过记忆和泛化（memorization and generalization），为用户推荐商品。该算法在Google Play上进行了实验和评估，结果表明，相比单一的宽线性模型和深度网络，该算法显著的提高了App安装量，具有更好的效果。另外，本文开源了一种基于Tens
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- 1. Wide & Deep Learning for Recommender Systems论文笔记
- 2. 论文笔记 - Wide & Deep Learning for Recommender Systems
- 3. 《Wide & Deep Learning for Recommender Systems》论文总结
- 4. 论文阅读：《Wide & Deep Learning for Recommender Systems》
- 5. Wide & Deep Learning for Recommender Systems
- 6. Wide &Deep Learning for Recommender Systems
- 7. #Paper Reading# Wide & Deep Learning for Recommender Systems
- 8. Wide & Deep Learning for Recommender Systems 翻译
- 9. Wide & Deep Learning for Recommender Systems 模型实践
- 10. Paper Reading:Wide & Deep Learning for Recommender Systems
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相关文章
- 1. Wide & Deep Learning for Recommender Systems论文笔记
- 2. 论文笔记 - Wide & Deep Learning for Recommender Systems
- 3. 《Wide & Deep Learning for Recommender Systems》论文总结
- 4. 论文阅读：《Wide & Deep Learning for Recommender Systems》
- 5. Wide & Deep Learning for Recommender Systems
- 6. Wide &Deep Learning for Recommender Systems
- 7. #Paper Reading# Wide & Deep Learning for Recommender Systems
- 8. Wide & Deep Learning for Recommender Systems 翻译
- 9. Wide & Deep Learning for Recommender Systems 模型实践
- 10. Paper Reading:Wide & Deep Learning for Recommender Systems