You are warmly invited to attend a talk by Francesca Panero. Details below.
Title: Sparse spatial random graphs
Where: USI Lugano East Campus, room D5.01, and online
When: 9 June, 12:30pm
We present a statistical model to describe spatial random graphs
through the graphex process, a construction which exploits the
Bayesian nonparametric framework in order to achieve flexibility and
interpretability when conducting inference. We provide a number of
asymptotic results, namely that the model is able to describe both
sparse and dense networks, is equipped with positive global and local
clustering coefficients and can achieve both single or double power
law degree distributions whose exponents are easily tuned. We present
a way to perform posterior inference through MCMC algorithms. Finally,
we place our proposal into the more general literature of spatial
random graphs, discussing the relations with hyperbolic random graphs,
scale-free percolation and sparse latent space models.
Francesca Panero is a visiting researcher at IDSIA and a DPhil
candidate in Statistics at the University of Oxford. She is working
with Prof. François Caron and Prof. Judith Rousseau on random graphs,
exploring both asymptotic properties of models based on graphex
processes and new modelling approaches to describe spatial networks.
Prior to this, she obtained a BSc and a MSc in Mathematics at the
University of Turin and Collegio Carlo Alberto.
Senior Researcher in Bayesian Networks and Graphical Models
Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA)
We are happy to announce the fourth talk of the series of webinars at IDSIA dedicated to the foundational, epistemological and ethical aspects of AI.
*Title: How values encroach on understanding from opaque machine learning models
*Abstract: How much is model opacity a problem for explanation and understanding from machine learning models? I argue that there are several ways in which non-epistemic values influence the extent to which model opacity undermines explanation and understanding. I consider three stages of the scientific process surrounding ML models where the influence of non-epistemic values emerges: 1) establishing the empirical link between the model and phenomenon, 2) explanation, and 3) attributions of understanding.
*Speaker: Emily Sullivan, Assistant Professor of Philosophy & Ethics, Department of Industrial Engineering & Innovation Sciences, Eindhoven University of Technology (personal webpage: http://www.eesullivan.com)
*Date: Thursday, June 10, 2021, at 17:00 (5pm) CET, on Zoom.
*Zoom Link: https://supsi.zoom.us/j/62374021896?pwd=WWNIKy9MVm9DNThHeHBpazdBS1YzQT09
ID meeting: 623 7402 1896
Apologies for cross-postings. Please find attached the invitation to an information meeting on AI topics in the forthcoming Horizon Europe and Digital Europe programmes.
The meeting will take blue on the 22nd of June 2021 at noon and it will be online (details in the attachment). I thank all the Euresearch team which has organised this presentation.
Istituto Dalle Molle di studi sull’intelligenza artificiale
Prof Dr Andrea Emilio Rizzoli
Polo universitario Lugano
Via la Santa 1
T +41 (0)58 666 66 64
F +41 (0)58 666 66 61