Byzantine-robust and efficient distributed sparsity learning: a surrogate composite quantile regression approach

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07) Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)
Nearly unbiased variable selection under minimax concave penalty
Statistics for high-dimensional data. Methods, theory and applications.
Composite quantile regression and the oracle model selection theory
One-step sparse estimates in nonconcave penalized likelihood models
A new perspective on robust $M$-estimation: finite sample theory and applications to dependence-adjusted multiple testing
Robust sub-Gaussian estimation of a mean vector in nearly linear time
Robust machine learning by median-of-means: theory and practice
Robust classification via MOM minimization
Adaptive robust variable selection
Robust Decoding from 1-Bit Compressive Sampling with Ordinary and Regularized Least Squares
Adaptive Huber Regression
The Byzantine Generals Problem
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
Local Composite Quantile Regression Smoothing: An Efficient and Safe Alternative to Local Polynomial Regression
Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)
Robust Estimation via Robust Gradient Estimation
Statistical Foundations of Data Science
Sparse Composite Quantile Regression in Ultrahigh Dimensions With Tuning Parameter Calibration
Communication-Efficient Distributed Statistical Inference
A review of distributed statistical inference
Robust Statistics
Distributed Sparse Composite Quantile Regression in Ultrahigh Dimensions
Communication-Efficient Accurate Statistical Estimation
ADMM for High-Dimensional Sparse Penalized Quantile Regression

This page was built for publication: Byzantine-robust and efficient distributed sparsity learning: a surrogate composite quantile regression approach

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6606957)