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論文《Unsupervised Continual Learning And Self-Taught Associative Memory Hierarchies》解讀
時間 2021-01-15
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本論文提出了一個無監督的持續學習組件STAM(Self-Taught Associative Memory) 如下圖: 上圖中, C i C_i Ci爲所有聚類簇的集合。當一個圖片 X i X_i Xi輸入到這個結構中時,會被打碎成若干個重疊的可接受域(Receptive Fields,RFs)。需要注意的是,每一個STAM結構處理一個可接受域。這些可接受域經過函數 c ( x i , m )
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相關文章
1.
【論文筆記】Continual Relation Learning via Episodic Memory Activation and Reconsolidation
2.
論文閱讀:Associative Embedding: End-to-End Learning for Joint Detection and Grouping
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4.
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6.
Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics 之論文詳解
7.
Supervised learning and Unsupervised learning
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Unsupervised Learning of Edges 論文閱讀
9.
論文閱讀: GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose(CVPR2018)
10.
論文閱讀——Mockingjay: unsupervised speech representation learning
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