arXiv · 2412.20747
Nonsmooth Convex Optimization using the Specular Gradient Method with Root-Linear Convergence
Abstract
We propose the specular gradient method for one-dimensional convex optimization. Assuming that the minimum is attained and a suitable initial distance bound holds, we establish R-linear convergence using normalized steps of geometrically decreasing length. Neither strong convexity nor differentiability is required.
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Kiyuob Jung, Jehan Oh. 2024-12-30. Nonsmooth Convex Optimization using the Specular Gradient Method with Root-Linear Convergence. https://arxiv.org/abs/2412.20747
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