Articles publiés

[1] Kengne, W. and Wade, M. : Deep learning from strongly mixing observations: Sparse-penalized regularization and minimax optimality 

                 Journal of Complexity (2025),

https://doi.org/10.1016/j.jco.2025.101978 

[2] Kengne, W. and Wade, M. : Robust deep learning from weakly dependent data. 

                    Neural Networks (2025),

https://doi.org/10.1016/j.neunet.2025.107227 

[3] Kengne, W. and Wade, M. : Sparse-penalized deep neural networks estimator under weak dependence.

                    Metrika (2024),

https://doi.org/10.1007/s00184-024-00965-1 

[4] Kengne, W. and Wade, M. : Deep learning for ψ-weakly dependent processes.

                    Journal of Statistical Planning and Inference (2024),

 https://doi.org/10.1016/j.jspi.2024.106163  

Prépublications

[1] Kengne, W. and Wade, M. :  A general framework for deep learning (submitted).

 [2] Kengne, W. and Wade, M. :  Deep regression learning from dependent observations with minimum error entropy principle (submitted)

[3] Kengne, W. and Wade, M. : Penalized deep neural networks estimators with general loss functions under weak dependence (submitted).