High-precision linear minimization is no slower than projection

Zev Woodstock

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arXiv · 2501.18454

High-precision linear minimization is no slower than projection

Zev Woodstock

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Abstract

This note demonstrates that, for all compact convex sets, high-precision linear minimization can be performed via a single evaluation of the projection and a scalar-vector multiplication. In consequence, if $\varepsilon$-approximate linear minimization takes at least $L(\varepsilon)$ real vector-arithmetic operations and projection requires $P$ operations, then $\mathcal{O}(P)\geq \mathcal{O}(L(\varepsilon))$ is guaranteed. This concept is expounded with examples, an explicit error bound, and an exact linear minimization result for polyhedral sets.

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Zev Woodstock. 2025-01-30. High-precision linear minimization is no slower than projection. https://arxiv.org/abs/2501.18454

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