論文閱讀筆記《Learning to remember rare events》
核心思想 本文提出一種終生記憶模塊（life-long memory module）能夠使得許多神經網絡實現單樣本學習，核心思想還是在訓練時將每個類別樣本的特徵信息與對應的標籤值保存下來，測試時利用最近鄰思想，選擇與查詢樣例最接近的K個樣本，並據此預測插敘樣例的標籤。記憶模塊由「鍵-值」對構成，「鍵」 K K K是神經網絡特定層的輸出，「值」 V V V則是給定樣本對應的標籤，此外還有一個額外
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相關文章
- 1. [paper] Learning to Remember Rare Events
- 2. [ICCV論文閱讀2019]Meta-Learning to Detect Rare Objects
- 3. Machine Learning & Deep Learning 論文閱讀筆記
- 4. 論文閱讀筆記《Deep Meta-Learning: Learning to Learn in the Concept Space》
- 5. 論文閱讀筆記《Meta-SGD: Learning to Learn Quickly for Few-Shot Learning》
- 6. 論文閱讀筆記《Learning to Compare: Relation Network for Few-Shot Learning》
- 7. Deep Mutual Learning論文閱讀筆記
- 8. 論文閱讀筆記《Active One-shot Learning》
- 9. 論文閱讀筆記《One-Shot Imitation Learning》
- 10. 論文閱讀筆記：Learning to Compose with Professional Photographs on the Web