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Fast Convolutional Neural Networ

Fast Convolutional Neural Networ

作者: Shuailong | 来源:发表于2016-07-11 11:32 被阅读209次

    Presented by: Xavier Bresson (Swiss Federal Institute of Technology) – Fast Convolutional Neural Networks for Graph-Structured Data

    Why CNNs work?

    Local stationary points.

    CNN for Graph Structured Data
    • Graph -> Euclidean Grid
    • Graph coarse -> Downsampling(pooling)
    Related work

    Categories of graph CNNs

    1. Spatial approach
    2. Spectral(Fourier) approach
    Convolution on Graph
    • Graph Laplace
    • Fourier transform on graph
    • Localized Filters
      Fast Chebyshev Polynomial Kernels
    Graph Coarsening
    • Graph partitioning: Balance Cut/Graclus
    • Fast Graph Pooling
    Optimization
    • Backpropagation
    • Gradient Descent
    Numeric Computation
    • Tensorflow
    • CUDA k40 (GPU x8 faster than CPU)
    Result
    • Euclidean CNNs
    • Non-Euclidean CNNs
    Future
    • Social networks
    • Gene networks
    • etc.

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