Nonsmooth Optimization-Based Hyperparameter-Free Neural Networks for Large-Scale Regression

Nonsmooth Optimization-Based Hyperparameter-Free Neural Networks for Large-Scale Regression

In this paper, a new nonsmooth optimization-based algorithm for solving large-scale regression problems is introduced. The regression problem is modeled as fully-connected feedforward neural networks with one hidden layer, piecewise linear activation, and the <inline-formula><math xmlns=&qu...

Full description

Bibliographic Details
Main Authors: Napsu Karmitsa, Sona Taheri, Kaisa Joki, Pauliina Paasivirta, Adil M. Bagirov, Marko M. Mäkelä
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Algorithms
Subjects:
machine learning
regression analysis
neural networks
L1-loss function
nonsmooth optimization
Online Access:https://www.mdpi.com/1999-4893/16/9/444

Internet

https://www.mdpi.com/1999-4893/16/9/444

Similar Items