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The solution of minimum energy can be approximated by the Graduated Non-Convexity (GNC) algorithm. The GNC approximates the non-convex solution space by a ...
The solution of minimum energy can be approximated by the Graduated Non-Convexity (GNC) algorithm. The GNC approximates the non-convex solution space by a ...
This work provides a method of finding the convex approximation to the solution space, and the convergent series of solution spaces, and it is proven, ...
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Mads Nielsen. Graduated Non-Convexity by Smoothness Focusing. In John Illingworth, editors, Proceedings of the British Machine Conference, pages 60.1-60.10.
This paper focuses on reducing the computational cost of a GNC Algorithm for deblurring images when dealing with full symmetric Toeplitz block matrices.
Sep 18, 2019 · In this paper, we enable the simultaneous use of non-minimal solvers and robust estimation by providing a general-purpose approach for robust global estimation.
Missing: Smoothness | Show results with:Smoothness
Abstract. The graduated optimization approach, also known as the continuation method, is a pop- ular heuristic to solving non-convex problems.
Missing: Smoothness | Show results with:Smoothness
Non-convex economies are studied with nonsmooth analysis, which is a generalization of convex analysis.
Oct 10, 2023 · This paper proposes a novel approach to GNC-based methods, focusing on the intricate relationship between the robust kernel's control parameter ...
Missing: Smoothness | Show results with:Smoothness
In this paper, we further generalize this non-uniform smoothness condition and develop a simple, yet powerful analysis technique that bounds the gradients along ...