One-dimensional worst-case conjecture for gradient descent on composed operator classes

Let Cμg0\mathcal{C}_{\mu_g}^{0} and DμgμM\mathcal{D}_{\mu_g}^{\mu_M} be the operator-composed function classes defined in the source, and let Cμg0,(1)\mathcal{C}_{\mu_g}^{0,(1)} and DμgμM,(1)\mathcal{D}_{\mu_g}^{\mu_M,(1)} denote their subclasses with one-dimensional gg and scalar linear operator MM. One-dimensional worst-case conjecture. The worst-case performances are attained in these one-dimensional subclasses:

w(Cμg0;h)=w(Cμg0,(1);h),w(DμgμM;h)=w(DμgμM,(1);h).w(\mathcal{C}_{\mu_g}^{0};h)=w(\mathcal{C}_{\mu_g}^{0,(1)};h),\qquad w(\mathcal{D}_{\mu_g}^{\mu_M};h)=w(\mathcal{D}_{\mu_g}^{\mu_M,(1)};h).

The conjecture is motivated by the authors' numerical experiments, but the supplied text gives no proof or resolution.

Sources & referencesView supporting material

Primary source

Nizar Bousselmi, Julien M. Hendrickx and François Glineur, “Interpolation Conditions for Linear Operators and Applications to Performance Estimation Problems”, arXiv:2302.08781 (2024).

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