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Home work in python using cvxpy to Stephen Boyd's Convex Optimization class (CVX101 Stanford)

Python 0.10% MATLAB 0.08% Jupyter Notebook 99.81%

convex-optimization-with-python's Introduction

CVX101 - Convex Optimization HW with python

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

Important links

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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