<A Critical Review of Recurrent Neural Networks for Sequence Learning>閱讀筆記
最近要學習RNN相關知識，根據知乎的建議，首先閱讀了這篇經典論文。邊讀邊想遍記錄。 一、3個問題 1. 爲什麼一定要是序列模型？ 像SVM、LR、前向反饋網絡是建立在 「獨立」假設的基礎上，更多模型則是人爲地去構造前後順序。但即使這樣，上述模型仍然不能解決長時間序列的依賴問題。比如語音或文本識別中的長句子場景。 所以，這種有時間或順序性的模型，是不能用幾個分類器或學習模型串聯起來進行等價的。 對於
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相關文章
- 1. A Critical Review of Recurrent Neural Networks for Sequence Learning
- 2. 論文閱讀：A Critical Review of Recurrent Neural Networks for Sequence Learning
- 3. 論文解讀A Critical Review od Recurrent Neural Networks for Sequence Learning
- 4. Recurrent Neural Networks Tutorial閱讀筆記
- 5. 《Graph Neural Networks: A Review of Methods and Applications》閱讀筆記
- 6. Graph Neural Networks: A Review of Methods and Applications閱讀筆記
- 7. Supervised Sequence Labelling with Recurrent Neural Networks 筆記 -LSTM
- 8. A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction閱讀筆記
- 9. LSTM Recurrent Neural Networks for Short Text and Sentiment Classication文章閱讀筆記
- 10. 【閱讀筆記】《ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks》