A collection of tutorials for the MOSEK package. Compatible with the current stable version of MOSEK.
The provided material complements the official MOSEK documentation with case studies, step-by-step tutorials and other material that may not fit otherwise.
Many notebooks are accompanied by source code files and other material. Please browse the relevant directory.
Python notebooks use MARIMO. Links for direct online viewing are available on the MOSEK documentation page.
- Introduction to Fusion
- Least squares regression
- Linear regression techniques
- Rank-one convexification for sparse regression
- Hierarchical model
- Max Volume Cuboid
- MLE convex density function
- GP Toolbox
- Stochastic risk measures
- Irreducible Infeasible Subset (IIS)
- Unit commitment
- SINR Optimization
- Filter design
- K-means and Euclidean Clustering
- Binary quadratic problems
- Subcarrier and power allocation
- Geometric facility location
- Smallest enclosing ellipsoid
- Truss topology design
- Optimization of cycles on surfaces
- Equilibrium of masses with springs
- Exact planar cover
- Approximating uncertain inequalities
- Wasserstein barycenter
- Wasserstein barycenter with regularization
- Wasserstein barycenter (Julia)
- Wasserstein barycenter with regularization (Julia)
- Utility based option pricing
- Piecewise linear approximation of a convex function
- Distributionally robust portfolio
This work is licensed under a Creative Commons Attribution 4.0 International License. The MOSEK logo and name are trademarks of Mosek ApS. The code is provided as-is. Compatibility with future release of MOSEK or the Fusion API are not guaranteed. For more information contact our support.