optimization

Randomized Greedy Algorithms for Neural Network Optimization in Solving Partial Differential Equations

Xiaofeng Xu, Ph.D. Student, Applied Mathematics and Computational Sciences

Jul 15, 17:00 - 19:00

B4 L5 R5220

PDEs optimization machine learning randomized orthogonal greedy algorithm

This thesis introduces the randomized orthogonal greedy algorithm (ROGA) to bridge the gap between theoretical and practical performance of shallow neural networks for solving partial differential equations by overcoming key optimization challenges to achieve provably optimal convergence rates.

Chengjie zhao

Chengjie Zhao

Visiting Researcher, Information Science Lab

Wireless communication Signal processing optimization machine learning

Visiting Student, King Abdullah University of Science and Technology

Chaabane Mankai

M.S. Student, Electrical and Computer Engineering

Wireless Communications optimization Performance analysis network security

Surrounded by bright minds and groundbreaking research, KAUST is a great place to learn and grow.

Ahmed Youssef Ragab Radwan

Visiting Student (former), Information Science Lab

artificial intelligence TinyML optimization deep learning

Visiting student at the Information Science Lab, in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST)