positive semidefinite programming
[/ˈpɒzətɪv ˌsemiˈdefɪnət ˈproʊɡræmɪŋ/]
noun
programação semidefinida positiva
1. A subfield of convex optimization dealing with optimization problems where the constraints and/or objective function involve positive semidefinite matrices
Positive semidefinite programming is used to solve robust optimization problems where uncertainty must be accounted for.
A programação semidefinida positiva é utilizada para resolver problemas de otimização robusta onde a incerteza deve ser considerada.
2. An optimization technique where decision variables are constrained to be positive semidefinite matrices, often represented as X ≽ 0
The algorithm finds the optimal positive semidefinite matrix that minimizes the objective function.
O algoritmo encontra a matriz semidefinida positiva ótima que minimiza a função objetivo.
This is a specialized mathematical term primarily used in academic and professional contexts in optimization, control theory, and operations research. It is not commonly used in everyday conversation in either English or Portuguese-speaking regions, but is standard terminology in universities and research institutions worldwide.
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