[HTML][HTML] Bayesian learning of feature spaces for multitask regression
C Sevilla-Salcedo, A Gallardo-Antolín… - Neural Networks, 2024 - Elsevier
This paper introduces a novel approach to learn multi-task regression models with
constrained architecture complexity. The proposed model, named RFF-BLR, consists of a …
constrained architecture complexity. The proposed model, named RFF-BLR, consists of a …
[PDF][PDF] ENSOCOM: Ensemble of Multi-Output Neural Network's Components for Multi-Label Classification.
KM Alzhrani - Computers, Materials & Continua, 2022 - cdn.techscience.cn
Multitasking and multioutput neural networks models jointly learn related classification tasks
from a shared structure. Hard parameters sharing is a multitasking approach that shares …
from a shared structure. Hard parameters sharing is a multitasking approach that shares …