EE 364A: Convex Optimization

Stanford course with 17 lecture notes.

Lecture Timeline

• 2025-01-06 — SU-EE364a JAN062026
• 2025-03-03 — SU-EE364A MAR032026
• 2026-01-08 — SU-EE364A JAN082026
• 2026-01-13 — SU-EE364A JAN132026
• 2026-01-15 — SU-EE364A JAN152026
• 2026-01-20 — SU-EE364A JAN202026
• 2026-01-22 — SU-EE364A JAN222026
• 2026-01-27 — SU-EE364A JAN272026
• 2026-02-02 — SU-EE364A FEB022026
• 2026-02-03 — SU-EE364A FEB032026
• 2026-02-05 — SU-EE364A FEB052026
• 2026-02-10 — SU-EE364A FEB102026
• 2026-02-19 — SU-EE364A FEb192026
• 2026-02-24 — SU-EE364A FEB242026
• 2026-02-26 — SU-EE364A FEB262026
• 2026-03-05 — SU-EE364A MAR052026
• 2026-03-10 — SU-EE364A MAR102026

Key Topics Referenced

• Approximation And Fitting
• Centering
• Complementary Slackness
• Conjugate Function
• Constructive Convexity Verification
• Convergence Of Self Concordant Functions
• Convex Functions
• Convex Optimization
• Convex Problem Hiearchy
• Convex Problems
• Convex Sets
• Convexity Preserve Line Restriction
• Cvxpy
• Descent Method
• Diciplined Convex Programming
• Dual Transformation
• Duality For Feasible Problems
• Equality Constrained Minimization
• Extended Value Extension
• Farkas Lemma
• Function Convexity Conditions
• Geometric Interperattion Of The Dual
• Geometric Programming
• Interior Point Method
• Iterative Method
• Jensen S Inequality
• Linear Constraint Optimization
• Maximum Likelihood Estimation With Convex Optimization
• Minimum Volume Elipsolid
• Non Linear Optimization