Saddle-Point Optimality: A Look Beyond Convexity
Journal of Global Optimization
Deterministic Global Optimization: Theory, Methods and (NONCONVEX OPTIMIZATION AND ITS APPLICATIONS Volume 37) (Nonconvex Optimization and Its Applications)
Introduction to Mathematical Programming: Applications and Algorithms
Introduction to Mathematical Programming: Applications and Algorithms
A review of recent advances in global optimization
Journal of Global Optimization
Convexification for data fitting
Journal of Global Optimization
Convergence rate of McCormick relaxations
Journal of Global Optimization
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It is well known that a twice continuously differentiable function can be convexified by a simple quadratic term. Here we show that the convexification is possible also for every Lipschitz continuously differentiable function. This implies that the Liu---Floudas convexification works for, loosely speaking, almost every smooth program occurring in practice.