EGD statistical-radius conjecture in the middle SNR regime

From papers

Let the generalized linear model have link-function power p=2p=2, and let the true parameter θ\theta^{*} satisfy

C1(d/n)1/4θC2,C_{1}(d/n)^{1/4}\leq \lVert\theta^{*}\rVert\leq C_{2},

where C1C_{1} and C2C_{2} are universal constants. Let the EGD initialization satisfy θn0B(θ,ρ)\theta_n^0\in\mathbb{B}(\theta^{*},\rho) for a constant ρ\rho.

EGD statistical-radius conjecture. There exist universal constants C3,C4,C5C_{3},C_{4},C_{5} such that, whenever nC3(dlog(d/δ))4n\geq C_{3}(d\log(d/\delta))^{4} and tC4log(n/(d+log(1/δ)))t\geq C_{4}\log(n/(d+\log(1/\delta))), with probability 1δ1-\delta,

min1ktθnkθC51θdn.\min_{1\leq k\leq t}\lVert\theta_n^k-\theta^{*}\rVert\leq C_{5}\frac{1}{\lVert\theta^{*}\rVert}\sqrt{\frac{d}{n}}.

This conjecture would provide a logarithmic-iteration statistical guarantee for EGD in the middle SNR regime, matching the expected computational advantage over GD. The paper notes that establishing the required homogeneous assumption for the population loss is the main obstacle, so the claim remains open.

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Sources & referencesView supporting material

Primary source

Nhat Ho, Tongzheng Ren, Sujay Sanghavi, Purnamrita Sarkar and Rachel Ward, “An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models”, arXiv:2205.07999 (2023).

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