Syllabus

The following topics will be covered, subject to changes. See the course web page for a detailed schedule.

• Mathematics of Convex Optimization
  • Linear Algebra review (SVD, other matrix decompositions)
  • Review: Norms
  • Convex Sets
  • Convex Functions
  • Convex Optimization Problems
  • Duality
• Applications of Convex Optimization
  • Approximation and Fitting
  • Statistical Estimation
  • Geometric Problems
• *Algorithms
  • Numerical Linear Algebra and Complexity
  • Unconstrained Minimization
  • Equality Constrained Minimization
  • Interior Point Methods
  • Conjugate Gradient Method
  • Accelerated Gradient Method
  • Stochastic Gradient Descent
  • Natural Gradient Descent
  • RMSprop and Adam