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