This talk on Convex Optimization was held on Friday October 28, 2016 in MC 4020. The talk was given by Rolina Wu.


This talk will introduce the basics for Convex Optimization, several popular optimization algorithms, and the application for convex optimization in Machine Learning.

Boyd and Vandenberghe, 2004 will be used for reference.


  • Introduction(definition of Affine, Convex Sets, Convex functions, Conic Combinations, Convex Cones, and Convex Hulls)

    • The main focus will be on Affine, Convex functions, Convex and Conic hulls.

  • Extreme points

  • Subdifferentials

  • Convex Minimization + Maximization

  • Applications:

    • Perceptron

    • Gradient Descent

      • How it is used in Machine Learning algorithms