Reinforcement Learning

Training Neural Networks at Any Scale

Volkan Cevher, Associate Professor, School of Engineering, Swiss Federal Institute of Technology (EPFL), Switzerland

Nov 24, 12:00 - 13:00

B9 L2 R2325

machine learning Numerical simulation and analysis Reinforcement Learning deep learning optimization

The talk explores a key mathematical ingredient of scaling in tandem with scaling theory: the numerical solution algorithms commonly employed in deep learning, spanning domains from vision to language models.

Kaiqiang Lin

Postdoctoral Research Fellow, Electrical and Computer Engineering

Wireless Underground Sensor Networks LoRAWAN Space-Air-Ground-Underground Integrated Networks Wireless Energy Transfer Reinforcement Learning

Kaiqiang Lin is currently a Postdoctoral Research Fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), working with Professor Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Kaiqiang Lin received his B.Eng. degree in Electronic and Information Engineering from Fujian Agriculture and Forestry University, Fuzhou, China, in 2018, and his Ph.D. degree with the College of Surveying and Geo-Informatics Tongji University, Shanghai, China, in 2024. From 2021 to

Mohammed Alwagait

Ph.D. Student, Electrical and Computer Engineering

UAV adaptive control Reinforcement Learning Aerial Robotics

Mohammed is a PhD Student in the Electrical and Computer Engineering program (ECE) at KAUST. He focuses on Reinforcement Learning Based Energy Saving Path Planning and Control for UAVs.

Aznaur Aliev

M.S. Student

AI Deep learning Computer Vision Reinforcement Learning