Login to filter by course Login to filter by course Reset
Covers the principles of linear MM SE estimation and the minimization of errors in linear regression.
Covers the KKT conditions and convex optimization, discussing constraint qualifications and tangent cones of convex sets.
Covers an overview of convex optimization, affine sets, polyhedra, ellipsoids, and convex functions.
Explores static equilibrium modeling using nodes, forces, and bars, including force characteristics and the concept of force diagrams.
Explores diverse regularization approaches, including the L0 quasi-norm and the Lasso method, discussing variable selection and efficient algorithms for optimization.
