Latent Social Network Influence

Citation

S. A. Myers & J. Leskovec "On the Convexity of Latent Social Network Inference" In Neural Information Processing Systems (NIPS), 2010.

Online version

Link to paper

Summary

This paper is interesting paper of learning the graph structure which is not a typical Bayesian graph learning. The main problem that the authors try to solve is given a set of nodes and network diffusion, learn the graph over which the contagion spreads. Typically we observe the nodes getting infected and the time they get infected, however we cannot know who infected them. This problem is converted to a maximum likelihood based convex optimization problem and further they introduce an $l_{1}$ penalty to penalize the graph with larger number of nodes.