Distributed optimal subsampling for quantile regression with massive data

Cites Work

Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
CUR matrix decompositions for improved data analysis
Distributed subdata selection for big data via sampling-based approach
Composite quantile regression and the oracle model selection theory
On the de la Garza phenomenon
Bootstrap methods: another look at the jackknife
A distributed one-step estimator
Limiting distributions for \(L_1\) regression estimators under general conditions
Optimal subsampling for large-scale quantile regression
The cost of privacy: optimal rates of convergence for parameter estimation with differential privacy
Optimal subsampling for composite quantile regression in big data
Optimal subsample selection for massive logistic regression with distributed data
Optimal subsampling for composite quantile regression model in massive data
Block average quantile regression for massive dataset
Information-based optimal subdata selection for big data logistic regression
Quantile regression under memory constraint
Quantile regression in big data: a divide and conquer based strategy
Distributed inference for quantile regression processes
Efficient resampling methods for nonsmooth estimating functions
Sampling algorithms for l₂ regression and applications
Regression Quantiles
Asymptotic Statistics
Minimax Optimal Procedures for Locally Private Estimation
Optimal Subsampling for Large Sample Logistic Regression
GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning
Privacy-Preserving Parametric Inference: A Case for Robust Statistics
Advances and Open Problems in Federated Learning
Heterogeneity-aware and communication-efficient distributed statistical inference
Least-Square Approximation for a Distributed System
Optimal subsampling for linear quantile regression models
Information-Based Optimal Subdata Selection for Big Data Linear Regression
A Statistical Framework for Differential Privacy
Optimal subsampling for quantile regression in big data
Gaussian Differential Privacy
Optimal subsampling for large‐sample quantile regression with massive data
Communication-efficient surrogate quantile regression for non-randomly distributed system
Network Gradient Descent Algorithm for Decentralized Federated Learning
A Note on Distributed Quantile Regression by Pilot Sampling and One-Step Updating
Communication-efficient estimation and inference for high-dimensional quantile regression based on smoothed decorrelated score

This page was built for publication: Distributed optimal subsampling for quantile regression with massive data