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Can I read Conditions for Exact Convex Relaxation and No Spurious Local Optima on EtoBox?
Conditions for Exact Convex Relaxation and No Spurious Local Optima by Fengyu Zhou; Steven H. Low is a Computer Science article available to read on EtoBox.
What is Conditions for Exact Convex Relaxation and No Spurious Local Optima about?
Nonconvex optimization problems can be approximately solved via relaxation or local algorithms. For many practical problems such as optimal power flow (OPF) problems, both approaches tend to succeed in the sense that relaxation is usually exact and local algorithms usually converge to a global optimum. In this article, we study conditions that are sufficient or necessary for such nonconvex problems to simultaneously have exact relaxation and no spurious local optima. These conditions help explain the widespread empirical experience that OPF problems, even though computationally hard in theory, seem to be easy in practice.
Who reads Conditions for Exact Convex Relaxation and No Spurious Local Optima?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Fengyu Zhou; Steven H. Low
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Published
- 2022
- Language
- EN
- Field
- Computer Science (Physical Sciences)