A review of distributed statistical inference
From MaRDI portal
Publication:5880109
DOI10.1080/24754269.2021.1974158OpenAlexW3200669006MaRDI QIDQ5880109
No author found.
Publication date: 7 March 2023
Published in: Statistical Theory and Related Fields (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/24754269.2021.1974158
bootstrapprincipal component analysisdistributed computingnonparametric estimationshrinkage methodsdivide-and-conquerfeature screeningcommunication-efficiency
Related Items
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Model-Free Feature Screening for Ultrahigh-Dimensional Data
- A partially linear framework for massive heterogeneous data
- Divide and conquer local average regression
- Subsampling
- Distributed testing and estimation under sparse high dimensional models
- Distributed kernel-based gradient descent algorithms
- Distributed statistical estimation and rates of convergence in normal approximation
- Distributed estimation of principal eigenspaces
- Quantile regression under memory constraint
- Quantile regression in big data: a divide and conquer based strategy
- Projected spline estimation of the nonparametric function in high-dimensional partially linear models for massive data
- Distributed inference for quantile regression processes
- Distributed learning with multi-penalty regularization
- Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates
- Confidence Intervals and Hypothesis Testing for High-Dimensional Regression
- A split-and-conquer approach for analysis of
- Differential Privacy: A Survey of Results
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- On the optimality of averaging in distributed statistical learning
- Sure Independence Screening for Ultrahigh Dimensional Feature Space
- Computational Limits of A Distributed Algorithm For Smoothing Spline
- A Scalable Bootstrap for Massive Data
- Communication-Efficient Distributed Statistical Inference
- Resampling Fewer Than n Observations: Gains, Losses, and Remedies for Losses
- Multivariate Meta-Analysis of Heterogeneous Studies Using Only Summary Statistics: Efficiency and Robustness
- A Split-and-Merge Bayesian Variable Selection Approach for Ultrahigh Dimensional Regression
- Learning Bounds for Kernel Regression Using Effective Data Dimensionality
- Meta-analysis of independent datasets using constrained generalised method of moments
- A general theory of concave regularization for high-dimensional sparse estimation problems
- Distributed Estimation for Principal Component Analysis: An Enlarged Eigenspace Analysis
- First-Order Newton-Type Estimator for Distributed Estimation and Inference
- Communication-Efficient Accurate Statistical Estimation
