LLM

KAUST advances scalable AI through global collaboration

1 min read · Wed, Nov 12 2025

machine learning LLM Federated learning Distributed algorithms

KAUST brings global experts together to advance scalable AI and tackle the challenges of training large models.

From the Ball-Proximal (Broximal) Point Method to Efficient Training of LLMs

Peter Richtarik, Professor, Computer Science

Sep 16, 16:00 - 17:00

B1 L3 R3119

AI machine learning optimization algorithms LLM

This talk introduces the Ball-Proximal Point Method, a new foundational algorithm for non-smooth optimization with surprisingly fast convergence, and Gluon, a new theoretical framework that closes the gap between theory and practice for modern LMO-based deep learning optimizers.

Ahmar Husain

Visiting Student, Computer, Electrical and Mathematical Sciences and Engineering

Cyber Security Malware Analysis LLM

From the Ball-Proximal (Broximal) Point Method to Efficient Training of LLMs

Peter Richtarik, Professor, Computer Science

Sep 4, 12:00 - 13:00

B9 L2 R2325

AI machine learning optimization algorithms LLM

This talk introduces the Ball-Proximal Point Method, a new foundational algorithm for non-smooth optimization with surprisingly fast convergence, and Gluon, a new theoretical framework that closes the gap between theory and practice for modern LMO-based deep learning optimizers.

Muhammad Samiullah

Intern, Cyber Security and Resilience Technology

cybersecurity ML FPGA LLM

Cyber Security, FPGA security, AI/ML security