[Statlist] Research Seminar in Statistics *FRIDAY 13 DECEMBER 2019* GSEM, University of Geneva

[gsem-support-instituts]

Dear All,

We are pleased to invite you to our next Research Seminar.

Looking forward to seeing you


Organizers :                                                                                   
E. Cantoni - S. Engelke - D. La Vecchia - E. Ronchetti
S. Sperlich - F. Trojani - M.-P. Victoria-Feser


FRIDAY 13 DECEMBER 2019 at 11:15am, Uni-Mail M 5220

Computationally Efficient Inference for Latent Position Network Models
Riccardo RASTELLI - University College Dublin, Ireland

ABSTRACT:
"Latent position models are widely used for the statistical analysis of networks in a variety of research fields. These models possess a number of desirable theoretical properties, and are particularly easy to interpret. However, algorithms that can fit these models generally require a computational cost which grows with the square of the number of nodes in the graph. This makes the analysis of large social networks impractical.

In this talk, I will show a new algorithm characterized by a linear computational complexity, which may be used to fit latent position models on networks of several tens of thousands nodes. The approach relies on an approximation of the likelihood function, where the amount of noise introduced can be arbitrarily reduced at the expense of computational efficiency. I will illustrate some theoretical results that show how the likelihood error propagates to the invariant distribution of the Markov chain Monte Carlo sampler. Finally, I will show some applications of the method to simulated networks and to a large network of coauthorships, demonstrating that one can achieve a substantial reduction in computing time and still obtain a reasonably good estimation of the latent structure."


Visit the website: https://www.unige.ch/gsem/en/research/seminars/rcs/