PALM-KQR combines inexact ADMM warm-start with semismooth Newton ALM and low-rank preconditioning to solve large-scale kernel quantile regression more efficiently than prior solvers.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Scalable Kernel Quantile Regression: A Preconditioned Augmented Lagrangian Method
PALM-KQR combines inexact ADMM warm-start with semismooth Newton ALM and low-rank preconditioning to solve large-scale kernel quantile regression more efficiently than prior solvers.