$l^\gamma$-pagerank for semi-supervised learning

HIGHLIGHTS

• who: Esteban Bautista from the , France have published the research: $L^gamma$-PageRank for Semi-Supervised Learning, in the Journal: (JOURNAL)
• what: As the first contribution, the authors propose a generalization of PageRank by using (non necessarily integers) powers of the combinatorial Laplacian matrix Lγ (γ > 0). The authors show that, for each γ, a new graph is generated. As a second contribution, the authors propose an algorithm that allows to estimate the optimal γ directly from the initial graph and the labeled points. Lastly, the authors demonstrate the classification improvements permitted by Lγ -PageRank on several real . . .
  

   

  

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