Media Summary: So we can define subgrading descent like before we just replace the gradient by Hope you will enjoy this video. I know my voiceover is lacking some emotion but i will try my best to improve that for my next video. I recommend you watch in 1.25x or 1.5x to not waste time.
W5 2 Subgradient And Subgradient - Detailed Analysis & Overview
So we can define subgrading descent like before we just replace the gradient by Hope you will enjoy this video. I know my voiceover is lacking some emotion but i will try my best to improve that for my next video. I recommend you watch in 1.25x or 1.5x to not waste time. Chapter 5: Convex Numerical algorithms 5.1: The F of X bar it is finite it's less than infinity okay an element V in R is current a ... vector V that satisfies this inequality is called a
This is a recorded lecture for the graduate-level course on convex optimization offered at UCSB Computer Science Department.
![[W5-2] subgradient and subgradient descent](https://i.ytimg.com/vi/3omfpgAxoFo/mqdefault.jpg)
![[CS292F 2020 Spring] Convex Optimization: Lecture 5 Subgradient](https://i.ytimg.com/vi/whXtMsrqBoo/mqdefault.jpg)
