Lecture 6 part 1: ADMM (basic definitions and properties)

This is Lecture 6- part 1 - of the KTH-EP3260 Fundamentals of Machine Learning over Networks (MLoNs), lectured by Euhanna Ghadimi. This lecture reviews the basics and recent advances of the alternating direction method of multipliers (ADMM) for large-scale machine learning problems. In particular, this lecture covers fundamentals of dual ascent, dual decomposition, proximal methods, augmented Lagrangian, ADMM, convergence results, and hyperparameter tuning.

Slides are available at the course website:
https://sites.google.com/view/mlons/course-materials

Видео Lecture 6 part 1: ADMM (basic definitions and properties) канала MLRG KTH