Examples -

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These examples show many different ways to use CVXPY.
The Basic examples section shows how to solve some common optimization problems in CVXPY.
The Disciplined geometric programming section shows how to solve log-log convex programs.
The Disciplined quasiconvex programming section has examples on quasiconvex programming.
The Derivatives section shows how to compute sensitivity analyses and gradients of solutions.
There are also application-specific sections.
The Basic applications section shows real-world applications of common optimization problems.
The Machine learning section is a tutorial on convex optimization in machine learning.
The Advanced and Advanced applications sections contains more complex examples for experts in convex optimization.
Most of these examples are implemented as Jupyter notebooks, while some are implemented as interactive marimo notebooks.
Additional examples are in the examples repository.
For geometric interpretations of linear and quadratic programs, see the marimo links.
Least squares [.ipynb] [marimo]
Linear program [.ipynb] [marimo]
Quadratic program [.ipynb] [marimo]
Semidefinite program [.ipynb] [marimo]
Disciplined convex programming
Mixed-integer quadratic program [.ipynb]
Minimum-fuel optimal control
Markowitz portfolio optimization
Beyond Markowitz portoflio optimization
Worst-case risk analysis
Total variation in-painting [.ipynb]
DGP fundamentals [.ipynb]
Maximizing the volume of a box [.ipynb]
Power control [.ipynb]
Perron-Frobenius matrix completion [.ipynb]
Rank-one nonnegative matrix factorization [.ipynb]
Concave fractional function [.ipynb]
Minimum-length least squares [.ipynb]
Hypersonic shape design [.ipynb]
Path planning with obstacles [.ipynb]
Sparse signal recovery [.ipynb]
Modelling chemical equilibrium [.ipynb]
Fundamentals [.ipynb]
Queuing design [.ipynb]
Structured prediction [.ipynb]
Ridge regression [.ipynb]
Lasso regression [.ipynb]