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Related lectures (32)

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Semi-Definite Programming

Covers semi-definite programming and optimization over positive semidefinite cones.

Two Inequalities and Feasible Cone: Linearized Approach

Explains feasible directions, linearized cone, and Constraint Qualification conditions in optimization.

Cones of convex sets

Explores optimization on convex sets, including KKT points and tangent cones.

Kernel Ridge Regression: Equivalent Formulations and Representer Theorem

Explores Kernel Ridge Regression, equivalent formulations, Representer Theorem, Kernel trick, and predicting with kernels.

Closed Surfaces and Integrals

Explains closed surfaces like spheres, cubes, and cones without covers, and their traversal and removal of edges.

Surface of Revolution

Explains the parametric equations of surfaces of revolution generated by curves in space.

Center of Mass: Hollow Cone Inertias

Covers center of mass in hollow cones with negative mass and direct methods.

Convex Optimization

Covers an overview of convex optimization, affine sets, polyhedra, ellipsoids, and convex functions.

Lagrangian Duality: Theory and Applications

Explores Lagrangian duality in convex optimization, discussing strong duality, dual solutions, and practical applications in second-order cone programs.

Projected Gradient Descent

Explores convex constrained optimization through Projected Gradient Descent, focusing on tangent space and iterative minimization.