1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.
News and Resources for Members of the IEEE Signal Processing Society
About the topic:
In many emerging applications, it is of paramount interest to learn hidden parameters from data. For example, self-driving cars may use onboard cameras to identify pedestrians, highway lanes, or traffic signs in various light and weather conditions. Problems such as these can be framed as classification, regression, or risk minimization, in general, at the heart of which lies stochastic optimization and machine learning. In many practical scenarios, distributed and decentralized learning methods are preferable as they benefit from a divide-and-conquer approach towards storage and computation at the expense of local (short-range) communication. In this talk, I will present our recent work that develops a novel algorithmic framework to address various aspects of distributed stochastic first-order optimization methods for non-convex problems. A major focus will be to characterize regimes where distributed solutions outperform their centralized counterparts and lead to optimal convergence guarantees. Moreover, I will characterize certain desirable attributes of distributed methods in the context of linear speedup and network- independent convergence rates. Throughout the talk, I will demonstrate such key aspects of the proposed methods with the help of provable theoretical results and numerical experiments on real data.
Usman A. Khan received the B.S. degree from University of Engineering and Technology, Pakistan, in 2002, the M.S. degree from University of Wisconsin-Madison, USA, in 2004, and the Ph.D. degree from Carnegie Mellon University, USA, in 2009, all in Electrical and Computer Engineering.
|Call for Nominations: IEEE Technical Field Awards||15 January 2024|
|Call for Officer Nominations: Vice President-Technical Directions||19 January 2024|
|Call for Nominations for IEEE SPS Editors-in-Chief||31 January 2024|
|Nominate an IEEE Fellow today!||7 February 2024|
© Copyright 2023 IEEE – All rights reserved. Use of this website signifies your agreement to the IEEE Terms and Conditions.
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.