A0495
Title: Nonparametric link prediction for networks and Bipartite graph
Authors: Jiashen Lu - University of Pittsburgh (United States)
Kehui Chen - University of Pittsburgh (United States) [presenting]
Abstract: A nonparametric link prediction framework for networks and Bipartite graphs is discussed. In particular, it will be discussed how to understand the missing mechanism and to deal with missing observations, when and how to use side information for link prediction, and how to improve the prediction accuracy for new entries (nodes). The proposed statistical framework leads to a simple algorithm with competitive performance.
