Collaborative Deep Learning for Recommender Systems
本文思路整理如下： 一， Contribution 二， 實驗 實際需求 訓練數據 實驗環境 2.1本文模型 模型訓練 模型輸出 2.2 實驗結果 《Collaborative Deep Learning for Recommender Systems》 目的：採用分層貝葉斯CDL構建模型，將深度學習SDAE和協同過濾結合起來，從而得以更精準推薦。 論文信息：香港理工大學王灝博士。 一，C
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相關文章
- 1. Collaborative Deep Learning for Recommender Systems
- 2. Deep Learning Architecture for Collaborative Filtering Recommender Systems
- 3. Wide & Deep Learning for Recommender Systems
- 4. Paper Reading:Wide & Deep Learning for Recommender Systems
- 5. Wide &Deep Learning for Recommender Systems
- 6. An Efficient Deep Learning Approach for Collaborative Filtering Recommender System
- 7. 論文筆記之 Collaborative Deep Learning for Recommender Systems
- 8. Wide & Deep Learning for Recommender Systems論文筆記
- 9. 《Wide & Deep Learning for Recommender Systems》論文總結
- 10. 論文筆記 - Wide & Deep Learning for Recommender Systems