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Optimization and Machine Learning
OML
Optimization and Machine Learning
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LLM

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.

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

Peter Richtarik, Professor, Computer Science
Sep 15, 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

Optimization and Machine Learning (OML)

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