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Complexity and Complexity Bounds
Complexity and Complexity Bounds
A fundamental property of the complexity metric developed by Ontonix is that it has bounds – a lower and an upper bound. This means that it cannot assume infinite values (both negative and positive). If it could it wouldn’t be a good metric.
All good metrics satisfy the laws of physics
For example, a temperature cannot go to infinity, or the density of a material cannot be negative. The…
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Foundations of Computational Mathematics - Random Gradient-Free Minimization of Convex Functions
Foundations of Computational Mathematics - Random Gradient-Free Minimization of Convex Functions #mathematics #convexoptimization #optimization #methods #complexity #bounds
From the journal, Foundations of Computational Mathematics, comes a paper on Random Gradient-Free Minimization of Convex Functions. This paper is free to read (link) through September 2019.
Abstract
In this paper, we prove new complexity bounds for methods of convex optimization based only on computation of the function value. The search directions of our schemes are normally distributed…
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