SybilFuse：Combining Local Attributes with Global Structure to Perform Robust Sybil Detect(論文筆記)
SybilFuse：Combining Local Attributes withGlobal Structure to Perform Robust Sybil Detection 1. 輸入數據 2. 訓練局部分類器 利用有區別的局部屬性（結構或內容）來訓練局部分類器。 2.1 局部節點分類器(Local node classifier ) 局部節點分類器預測每個節點的信任分數（Trust S
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相關文章
- 1. 【論文筆記】QANET：Combining Local Convolution With Global Self-attention for Reading Comprehension
- 2. 論文筆記：Improved Deep Embedded Clustering with Local Structure Preservation
- 3. 論文閱讀 Robust Facial Landmark Detection via a Fully-Convolutional Local-Global Context Network
- 4. Solving the Blind Perspective-n-Point ProblemEnd-To-End With Robust Differentiabl.....論文筆記
- 5. 【論文筆記】Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs
- 6. 【論文筆記】On How to Perform a Gold Standard Based Evaluation of Ontology Learning
- 7. GLAD: Global-Local-Alignment Descriptor for Pedestrian Retrieval 論文閱讀筆記
- 8. 《Learning Deep Representation for Face Alignment with Auxiliary Attributes》論文閱讀筆記
- 9. 【論文筆記】Robust Scene Text Recognition with Automatic Rectification
- 10. 論文筆記之Non-Local