CVX101 - Convex Optimization HW with python

Home Work to Stephen Boyd's Convex Optimization class (CVX101 Stanford) with python and cvxpy

Important links

• course home
• Convex optimization book
• CVX101 slides
• cvx home
• cvxpy home
• cvxpy examples
• cvxpy atomic functions
• cvxpy short course jpynb
• solution references in matlab
• stackexchange : Intuition about dual problem
• Problems data files python

Problem list of content

• HW3 Convex optimization problems
  • Q2 - "Hello World" in CVX
  • Q3 - Heuristic suboptimal solution for Boolean LP
  • Q4 - Protfolio optimization
• HW4 Duality
  • Q1 - Numerical perturbation analysis example
  • Q2 - A simple example
  • Q3 - Option Price Bounds
• HW5 Approximation and fitting
  • Q2 Fitting with censored data
  • Q3 Minimax rational fit to the exponential
• HW6 Statistical estimation
  • Q1 - Maximum likelihood estimation of an increasing nonnegative signal
  • Q2 - Worst-case probability of loss
• HW7 Geometric problems
  • Q1 - Three-way linear classification
  • Q2 - Fitting a sphere to data
  • Q3 - Learning a quadratic pseudo-metric from distance measurements
  • Q4 - Maximum volume rectangle inside a polyhedron
• HW9 Unconstrained minimization
  • Q1 - Gradient and Newton methods
  • Q2 - Basic portfolio optimization problem
  • Q3 - Sizing a gravity feed water supply network
  • Q4 - Flux balance analysis
  • Q5 - Online advertising dispaly
  • Q6 - Ranking by aggregating preference
• HW10 Equality constrained minimization
  • Q2 - Maximum likelihood prediction of team ability
  • Q3 - Allocation of interdiction effort

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