English

From Nesterov's Estimate Sequence to Riemannian Acceleration

Optimization and Control 2020-01-27 v1 Machine Learning

Abstract

We propose the first global accelerated gradient method for Riemannian manifolds. Toward establishing our result we revisit Nesterov's estimate sequence technique and develop an alternative analysis for it that may also be of independent interest. Then, we extend this analysis to the Riemannian setting, localizing the key difficulty due to non-Euclidean structure into a certain ``metric distortion.'' We control this distortion by developing a novel geometric inequality, which permits us to propose and analyze a Riemannian counterpart to Nesterov's accelerated gradient method.

Keywords

Cite

@article{arxiv.2001.08876,
  title  = {From Nesterov's Estimate Sequence to Riemannian Acceleration},
  author = {Kwangjun Ahn and Suvrit Sra},
  journal= {arXiv preprint arXiv:2001.08876},
  year   = {2020}
}

Comments

30 pages

R2 v1 2026-06-23T13:19:34.265Z