Youtube經典論文相關問題《Deep Neural Networks for YouTube Recommendations》
文章目錄 論文中召回階段都用了哪些特徵，哪些特徵令你印象深刻？ 論文排序階段用了哪些特徵，哪些特徵令你印象深刻？ 論文中訓練樣本怎麼設置的？ 論文中測試樣本是怎麼設置的？ 每一個備選video都會是一個分類，使用softmax訓練時有何改進？ 爲什麼不直接採用訓練時的model進行預測，而是採用了一種最近鄰搜索的方法？ 爲什麼不採取類似RNN的Sequence model，而是完全摒棄了用戶觀看歷
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相關文章
- 1. Deep Neural Networks for Object Detection論文翻譯
- 2. [論文解讀] Concolic Testing for Deep Neural Networks
- 3. 論文閱讀：Deep Neural Networks for Object Detection
- 4. Deep Learning 論文解讀——Session-based Recommendations with Recurrent Neural Networks
- 5. [deep compression] compressing deep neural networks 論文學習
- 6. Neural Networks and Deep Learning-引論
- 7. SESSION-BASED RECOMMENDATIONS WITH RECURRENT NEURAL NETWORKS論文解讀
- 8. Deep Neural Networks for Object Detection
- 9. Aggregated Residual Transformations for Deep Neural Networks
- 10. Neural Networks and Deep Learning -- Class 4: Deep Neural Networks