3 papers
stat.ML2026
Deep regression learning from dependent observations with minimum error entropy principle
William Kengne, Modou Wade
This paper considers nonparametric regression from strongly mixing observations. The proposed approach is based on deep neural networks with minimum error entropy (MEE) principle.…
math.ST2025
A general framework for deep learning
William Kengne, Modou Wade
This paper develops a general approach for deep learning for a setting that includes nonparametric regression and classification. We perform a framework from data that fulfills a g…
stat.ML2024
Robust deep learning from weakly dependent data
William Kengne, Modou Wade
Recent developments on deep learning established some theoretical properties of deep neural networks estimators. However, most of the existing works on this topic are restricted to…