mlsanityData to 14 Oct 2026

Deviation inequalities for stochastic approximation by averaging

arXiv 2102.08685 ↗First posted 17 Feb 2021math.PR math.OC stat.MLcited by 1

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Abstract (arXiv)

We introduce a class of Markov chains, that contains the model of stochastic approximation by averaging and non-averaging. Using martingale approximation method, we establish various deviation inequalities for separately Lipschitz functions of such a chain, with different moment conditions on some dominating random variables of martingale differences.Finally, we apply these inequalities to the stochastic approximation by averaging and empirical risk minimisation.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 2 of its 26 references that are in the map. First posted on arXiv 17 Feb 2021.

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2 of 26 references.

References · 2

  1. 2019High dimensional VAR with low rank transitioncited by 4
  2. 2018Exponential inequalities for nonstationary Markov Chainscited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Minimax estimation of the pseudo-spectral gap of continuous Markov chains, with applications to empirical concentration boundscited by 0