Semi-definite Programming

Semi-definite Programming (SDP) is a type of optimization where the goal is to find the best possible solution within certain rules, and the solution involves matrices that must be positive semi-definite—a condition meaning they don't produce negative values when used in specific calculations. It's used in fields like control systems, finance, and machine learning to handle problems with complex constraints efficiently. Essentially, SDP helps find optimal solutions when dealing with tasks that can be expressed through relationships involving matrices and inequalities, ensuring solutions are mathematically consistent and stable.