The RSS is pleased to be bringing back the popular journal webinar series. Featuring contributions from Hani Doss and Alain Durmus, we will begin by discussing Arnak S. Dalalyan’s 2017 Series B paper ‘Theoretical Guarantees for Approximate Sampling from Smooth and Log-Concave Densities’ on 31 October.
"[Dalalyan] combines techniques from convex optimisation with insights from random processes to provide non-asymptotic guarantees regarding the accuracy of sampling from a target probability density. These guarantees are notably simpler than those found in the existing literature, and they remain unaffected by dimensionality.
The findings pave the way for more widespread adoption of the mathematical and algorithmic tools developed in the field of convex optimization within the domains of statistics and machine learning."
Showcasing significant recent papers published in the Society’s journals, the journal webinar format aims to bring authors closer to their audience in academia and industry. Impactful features of the paper are presented by the author, followed by contributions from our guest discussants. Past webinars have welcomed high-profile authors including Brad Efron and Andrew Gelman.
The webinar is free and open to all, providing participants from anywhere in the world with the opportunity to discuss, question and comment on key journal papers in a welcoming and receptive environment.
Register
here.