Block cubic Newton with greedy selection

This repository contains the files related to the experiments reported in

A. Cristofari. Block cubic Newton with greedy selection. arXiv:2407.18150.

In this paper, a second-order block coordinate descent method is proposed, named Inexact Block Cubic Newton (IBCN) method, using a greedy rule for block selection and a cubic Newton strategy for block updates.

Author

Andrea Cristofari (e-mail: andrea.cristofari@uniroma2.it)

Licensing

IBCN is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. IBCN is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with IBCN. If not, see http://www.gnu.org/licenses/.

Usage

All codes are in Matlab. Two classes of unconstrained problems are considered, as described in the above paper.

1. For sparse least squares, run the file main_sp_ls.m.

2. For l2-regularized logistic regression, first download the datasets as indicated in the file main_l2_log_reg.m, then run it.