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Tight Lower Bounds under Asymmetric High-Order H\"older Smoothness and Uniform Convexity

Optimization and Control 2025-06-10 v3 Machine Learning

Abstract

In this paper, we provide tight lower bounds for the oracle complexity of minimizing high-order H\"older smooth and uniformly convex functions. Specifically, for a function whose pthp^{th}-order derivatives are H\"older continuous with degree ν\nu and parameter HH, and that is uniformly convex with degree qq and parameter σ\sigma, we focus on two asymmetric cases: (1) q>p+νq > p + \nu, and (2) q<p+νq < p+\nu. Given up to pthp^{th}-order oracle access, we establish worst-case oracle complexities of Ω((Hσ)23(p+ν)2(σϵ)2(qpν)q(3(p+ν)2))\Omega\left( \left( \frac{H}{\sigma}\right)^\frac{2}{3(p+\nu)-2}\left( \frac{\sigma}{\epsilon}\right)^\frac{2(q-p-\nu)}{q(3(p+\nu)-2)}\right) in the first case with an \ell_\infty-ball-truncated-Gaussian smoothed hard function and Ω((Hσ)23(p+ν)2+loglog((σp+νHq)1p+νq1ϵ))\Omega\left(\left(\frac{H}{\sigma}\right)^\frac{2}{3(p+\nu)-2}+ \log\log\left(\left(\frac{\sigma^{p+\nu}}{H^q}\right)^\frac{1}{p+\nu-q}\frac{1}{\epsilon}\right)\right) in the second case, for reaching an ϵ\epsilon-approximate solution in terms of the optimality gap. Our analysis generalizes previous lower bounds for functions under first- and second-order smoothness as well as those for uniformly convex functions, and furthermore our results match the corresponding upper bounds in this general setting.

Keywords

Cite

@article{arxiv.2409.10773,
  title  = {Tight Lower Bounds under Asymmetric High-Order H\"older Smoothness and Uniform Convexity},
  author = {Cedar Site Bai and Brian Bullins},
  journal= {arXiv preprint arXiv:2409.10773},
  year   = {2025}
}

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