normsconstrain
Normsconstrain is a concept in optimization and statistical modeling referring to restricting the magnitude of decision variables, parameters, or function outputs by enforcing a bound on their norm. The idea is to limit complexity, promote stability, and improve generalization by avoiding solutions with large or unbounded values. In practice, norms can be imposed as hard constraints or integrated into the objective through duality with regularization.
Mathematically, a normsconstrain often takes the form of a constraint such as ||x||_p ≤ t, where x
Normsconstrain contrasts with norm-based regularization, where a penalty proportional to a norm is added to the
Applications span machine learning, sparse modeling, compressed sensing, portfolio optimization, and control, where norm constraints help