Please join us at the Taskar Memorial Lecture 2018 – next Thursday, March 1st.
UNIVERSITY OF WASHINGTON
PAUL G. ALLEN SCHOOL OF COMPUTER SCIENCE & ENGINEERING
TASKAR MEMORIAL LECTURE
SPEAKER: Michael Jordan, University of California, Berkeley
TITLE: On Gradient-Based Optimization: Accelerated, Stochastic and Nonconvex
DATE: Thursday, March 1, 2018
TIME: 3:30 pm
HOST: Emily Fox
Many new theoretical challenges have arisen in the area of gradient-based optimization for large-scale statistical data analysis, driven by the needs of applications and the opportunities provided by new hardware and software platforms. I discuss several recent, related results in this area: (1) a new framework for understanding Nesterov acceleration, obtained by taking a continuous-time, Lagrangian/Hamiltonian/symplectic perspective, (2) a discussion of how to escape saddle points efficiently
in nonconvex optimization, and (3) the acceleration of Langevin diffusion.
Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley. His research interests bridge the computational, statistical, cognitive and biological sciences. Professor Jordan is a member of the National Academy of Sciences, a member of the National Academy of Engineering and a member of the American Academy of Arts and Sciences. He has been named a Neyman Lecturer and a Medallion Lecturer by the Institute of Mathematical Statistics. He received the IJCAI Research Excellence Award in 2016, the David E. Rumelhart Prize in 2015 and the ACM/AAAI Allen Newell Award in 2009.
Reception to take place in the Atrium, Paul G Allen Center for Computer Science & Engineering following the talk.
*NOTE* This lecture will be broadcast live via the Internet. See http://www.cs.washington.edu/news/colloq.info.html for more information.