The Application of Multi-block ADMM on Isotonic Regression Problems
Optimization and Control
2019-10-22 v2
Abstract
The multi-block ADMM has received much attention from optimization researchers due to its excellent scalability. In this paper, the multi-block ADMM is applied to solve two large-scale problems related to isotonic regression. Numerical experiments show that the multi-block ADMM is convergent when the chosen parameter is small enough and the multi-block ADMM scales well compared with baselines.
Cite
@article{arxiv.1903.01054,
title = {The Application of Multi-block ADMM on Isotonic Regression Problems},
author = {Junxiang Wang and Liang Zhao},
journal= {arXiv preprint arXiv:1903.01054},
year = {2019}
}
Comments
Accepted by 11th Workshop on Optimization for Machine Learning (OPT 2019), co-located with NeurIPS 2019