asynchronous algorithms

First Provably Optimal Asynchronous SGD for Homogeneous and Heterogeneous Data

Arto Maranjyan, Ph.D. Student, Computer Science

Dec 4, 08:30 - 11:00

B3/5 L0 A0125

machine learning optimization asynchronous algorithms Training

This thesis introduces a novel framework for asynchronous first-order stochastic optimization centered on heterogeneous worker speeds that remain fast, stable, and even provably optimal.

First Provably Optimal Asynchronous SGD for Homogeneous and Heterogeneous Data

Arto Maranjyan, Ph.D. Student, Computer Science

Nov 13, 12:00 - 13:00

B9 L2 R2325

machine learning optimization asynchronous algorithms Training

This talk will discuss how to design asynchronous optimization methods that remain fast, stable, and even provably optimal.

KAUST Research Workshop on Optimization and Big Data

Peter Richtarik, Professor, Computer Science

Feb 5, 08:00 - Feb 7, 05:00

B19 L3 H2

optimization machine learning Social Network Analysis asynchronous algorithms

The age of "big data" is here: data of unprecedented sizes is becoming ubiquitous, which brings new challenges and new opportunities. With this comes the need to solve optimization problems of unprecedented sizes.

Amani Alonazi

Visiting Researcher, Image and Video Understanding Lab

High Performance Computing asynchronous algorithms GPU Computing parallel algorithms performance modeling

Amani Alonazi is a Visiting Researcher in the Image and Viedo Understanding Lab (IVUL) Research Group working with Professor Bernard Ghanem. Previously, she was a Ph.D. candidate in Computer Science at CEMSE, KAUST, and a member of KAUST's Extreme Computing Research Center, ACM, and SIAM. Areas of expertise and current scientific interests Amani's research focuses on developing novel asynchronous task-based algorithms of solvers in scientific simulations. The core of her work lies within the domain of high-performance computing, which combines performance optimizations, modeling, and