Standard syllabus
Convex optimization · Graduate · Math
Topics
Convex analysis foundations
- Convex sets and convex functions; epigraphs and sublevel sets
- Separation theorems and supporting hyperplanes
- Subgradients and optimality conditions
- Conjugate functions and Fenchel duality
- Strong and strict convexity; smoothness and Lipschitz continuity
Convex optimization problems
- Linear, quadratic, and second-order cone programs
- Semidefinite programming (introduction)
- Duality theory: Slater conditions and KKT for convex problems
- Sensitivity and perturbation analysis
- Generalized inequalities and conic formulations
Algorithms
- Gradient descent and accelerated methods (Nesterov)
- Proximal methods and operator splitting
- Interior-point methods for LP and SDP (overview)
- ADMM and Douglas–Rachford splitting
- Complexity and convergence rates (introduction)
Pricing calculator
Choose materials, tutoring, or both — or book a single session as needed. Customize your plan on the subscribe page.
$1,162 · Convex optimization · 18 tutoring hrs
Study guides, worksheets, reviews, practice tests, and answer keys for 1 class. 18 tutoring hours (1 hr / week · semester). Bundle discount applied vs buying separately. Pay in full via Zelle or Venmo.