English

A note on concentration inequality for vector-valued martingales with weak exponential-type tails

Probability 2020-03-19 v3 Machine Learning

Abstract

We present novel martingale concentration inequalities for martingale differences with finite Orlicz-ψα\psi_\alpha norms. Such martingale differences with weak exponential-type tails scatters in many statistical applications and can be heavier than sub-exponential distributions. In the case of one dimension, we prove in general that for a sequence of scalar-valued supermartingale difference, the tail bound depends solely on the sum of squared Orlicz-ψα\psi_\alpha norms instead of the maximal Orlicz-ψα\psi_\alpha norm, generalizing the results of Lesigne & Voln\'y (2001) and Fan et al. (2012). In the multidimensional case, using a dimension reduction lemma proposed by Kallenberg & Sztencel (1991) we show that essentially the same concentration tail bound holds for vector-valued martingale difference sequences.

Keywords

Cite

@article{arxiv.1809.02495,
  title  = {A note on concentration inequality for vector-valued martingales with weak exponential-type tails},
  author = {Chris Junchi Li},
  journal= {arXiv preprint arXiv:1809.02495},
  year   = {2020}
}

Comments

This short note has been merged and integrated into a follow-up work arXiv:2003.03532. Communications on v2 are still welcome

R2 v1 2026-06-23T03:58:02.135Z