Online Seminar – July 2020 – Professor Michael I. Jordan – Optimization with Momentum

Joy Lukman

  • Friday
    3 July 2020
    8:00 am - 9:00 am

Event Time:
Friday, 3 July @ 0800 (AEST) (Melbourne)
Friday, 3 July @ 0600 (CST) (Beijing, China)
Friday, 3 July @ 0330 (IST) (New Delhi, India)
Thursday, 2 July @ 1500 (PDT) (Berkeley)
Thursday, 2 July @ 1800 (EDT) (New York)
Thursday, 2 July @ 2300 (BST) (London)

Presenter: Professor Michael I. Jordan, University of California, Berkeley

Biography:  UC Berkeley  &  Wikipedia

Topic:  Optimization with Momentum: Variational, Hamiltonian, and Symplectic Perspectives

Abstract: Many new mathematical challenges have arisen in the area of gradient-based optimization for large-scale statistical data analysis. I will argue that significant insight can be obtained by taking a continuous-time, variational perspective on optimization. Essentially we can obtain insight by formulating the question of the “optimal way to optimize”. Using a (dissipative) Hamiltonian formulation of the continuous-time dynamics, together with a particular discretization, I show how to obtain algorithms that preserve the favorable properties of the continuous-time dynamics. Moreover, I show how to obtain rate-matching lower bounds in continuous time. I’ll discuss both convex and nonconvex problems, and, time permitting, stochastic counterparts based on Langevin diffusions.

Structure: 45 minutes seminar with 15 minutes question time

Seminar Recording & Slides:


Please click here for the recording of the webinar.


Please click here for the presentation slides.