Exact(1)
We use the p-mean as a differentiable objective function in place of the maximum temperature.
Similar(59)
Optimizing for optimal VS performance results in a non differentiable objective function with multiple local optima.
In this paper, we formulate and study a new least-squares model that allows a monotone and differentiable objective function.
A regularized version of the Nikaido-Isoda function was first introduced in [8] for standard NEPs then further investigated by Heusinger and Kanzow [9], they reformulated the GNEP as a constrained optimization problem with continuously differentiable objective function.
A regularized version of the Nikaido-Isoda function was first introduced in [13] for NEPs then further investigated by Heusinger and Kanzow [14], they reformulated the GNEP as a constrained optimization problem with continuously differentiable objective function.
As Equations 15 to 18 are a convex optimization problem with differentiable objective and constraint, the KKT conditions are necessary and sufficient for the optimality.
A derivative-free coordinate search method is employed to optimize a non-differentiable objective function.
Indeed, consider the steady-state condition and regard it as a differentiable map (x1, x2) → (c1, c2).
The expression of the l p sparsity regularization is reformulated as a differentiable function of a parameter to avoid the difficulty in calculating its gradient in the optimization process.
Intuitively, the algorithm works much like a standard gradient descent procedure adapted for non-differentiable objective functions, but with the added twist that the projection operation ensures that the weight vector iterates stay with a region of the parameter space where the optimum is known to exist.
The proposed algorithm can optimize complex, comprehensive, and non-differentiable objective function.
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