Distributed function estimation: adaptation using minimal communication
From MaRDI portal
Publication:2694726
DOI10.4171/MSL/33MaRDI QIDQ2694726
Harry van Zanten, Botond Szabó
Publication date: 4 April 2023
Published in: Mathematical Statistics and Learning (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2003.12838
Besov spacesadaptationnonparametric estimationminimax ratescommunication constraintsdivide-and-conquer methods
Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Information theory (general) (94A15)
Related Items (2)
Optimal high-dimensional and nonparametric distributed testing under communication constraints ⋮ Bayes in action in deep learning and dictionary learning
Cites Work
- Unnamed Item
- Adaptive confidence sets in \(L^2\)
- Wavelets on the interval and fast wavelet transforms
- Wavelets, approximation, and statistical applications
- Distributed testing and estimation under sparse high dimensional models
- An adaptation theory for nonparametric confidence intervals
- Adaptive confidence interval for pointwise curve estimation.
- Honest adaptive confidence bands and self-similar functions
- Distributed nonparametric function estimation: optimal rate of convergence and cost of adaptation
- Asymptotic frequentist coverage properties of Bayesian credible sets for sieve priors
- Adaptive distributed methods under communication constraints
- Testing the regularity of a smooth signal
- Confidence bands in density estimation
- Adaptive nonparametric confidence sets
- Frequentist coverage of adaptive nonparametric Bayesian credible sets
- Mathematical Foundations of Infinite-Dimensional Statistical Models
- On the optimality of averaging in distributed statistical learning
- A Scalable Bootstrap for Massive Data
- Optimal Distributed Composite Testing in High-Dimensional Gaussian Models With 1-Bit Communication
- An asymptotic analysis of distributed nonparametric methods
- Communication lower bounds for statistical estimation problems via a distributed data processing inequality
This page was built for publication: Distributed function estimation: adaptation using minimal communication
