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Semi-Supervised Learning With Graphs

Semi-Supervised Learning With Graphs. William Cohen. Section outline: SSL and Graphs. PageRank - how to scale it RWR/Personalized PageRank approximate Personalized PageRank plus a “sweep” - extract a subcommunity in a graph, for sampling purposes

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Semi-Supervised Learning With Graphs

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  1. Semi-Supervised Learning With Graphs William Cohen

  2. Section outline: SSL and Graphs • PageRank - how to scale it • RWR/Personalized PageRank • approximate Personalized PageRank • plus a “sweep” - extract a subcommunity in a graph, for sampling purposes • RWR for SSL classification of network data • MultiRankWalk method • “Harmonic field”/wvRN/Co-EM baseline • Modified Adsorption and SSL • SSL on graphs as an optimization problem • Unsupervised learning on graphs • Learning on graphs for non-graph datasets • unsupervised and semi-supervised

  3. Modified Adsorption

  4. More on SSL on graphsfrom ParthaTalukdar

  5. How to do this minimization? • First, differentiate to find min is at • Jacobi method: • To solve Ax=b for x • Iterate: • … or:

  6. Graph: connect each documentto its K nearest neighbors

  7. Graph: connect each documentto its K nearest neighbors

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