Zoom Link: https://snu-ac-kr.zoom.us/my/youngjoonhong 

The alternating direction method of multipliers (ADMM) is a classical optimization algorithm with a wide range of applications and a large user base. Although ADMM was originally developed in the 1970s, its popularity rose in the modern era of the 2010s with the advent of large-scale computing and data-driven applications. In this talk, we discuss recent post-modern advances of ADMM. We first introduce function-linearized proximal ADMM (FLiP-ADMM), where the linearization mechanism significantly broadens the target class of problems. Then, we introduce Adaptive Linearized ADMM (ALiA), where the adaptivity mechanism enhances the speed and the usability of the algorithm.