mlsanityData to 14 Oct 2026

Distributed Statistical Estimation and Rates of Convergence in Normal Approximation

arXiv 1704.02658 ↗First posted 9 Apr 2017math.ST cs.DC stat.MLcited by 15

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Abstract (arXiv)

This paper presents a class of new algorithms for distributed statistical estimation that exploit divide-and-conquer approach. We show that one of the key benefits of the divide-and-conquer strategy is robustness, an important characteristic for large distributed systems. We establish connections between performance of these distributed algorithms and the rates of convergence in normal approximation, and prove non-asymptotic deviations guarantees, as well as limit theorems, for the resulting estimators. Our techniques are illustrated through several examples: in particular, we obtain new results for the median-of-means estimator, as well as provide performance guarantees for distributed maximum likelihood estimation.

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Apr 2017.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 3; 2022: 3; 2023: 2; 2024: 2; 2025: 4; 2026: 1.

15 papers.

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  1. 2022Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challengescited by 138
  2. 2021Variance Reduced Median-of-Means Estimator for Byzantine-Robust Distributed Inferencecited by 11
  3. 2022Bandits Corrupted by Nature: Lower Bounds on Regret and Robust Optimistic Algorithmcited by 6
  4. 2023Machine Learning and the Future of Bayesian Computationcited by 4
  5. 2023Optimality in Mean Estimation: Beyond Worst-Case, Beyond Sub-Gaussian, and Beyond 1+α Momentscited by 4
  6. 2021Distributed Sparse Normal Means Estimation with Sublinear Communicationcited by 3
  7. 2025Robust Score Matchingcited by 2
  8. 2022Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraintscited by 1
  9. 2024Byzantine-tolerant distributed learning of finite mixture modelscited by 1
  10. 2021Divide-and-conquer methods for big data analysiscited by 0
  11. 2024Classical Shadows with Improved Median-of-Means Estimationcited by 0
  12. 2025Learning Centre Partitions from Summariescited by 0
3 more
  1. 2025On the Optimality of the Median-of-Means Estimator under Adversarial Contaminationcited by 0
  2. 2025Robust Variational Bayes by Min-Max Median Aggregationcited by 0
  3. 2026HOMER: Huber-of-Means for Efficient and Robust Estimation in Hilbert Spacescited by 0