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20232026
most citedPenalized deep neural networks estimator with general loss functions under weak dependence

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

math.ST2026

Max-Stable Survival Copulas under Dependent Censoring: Sharp Identification and Efficient Inference

Djibril Gueye, Salima Helali, Modou Wade

We study dependent censoring within a generalized Cox first-hitting-time. framework based on compensator reductions. In the genuinely dependent case, we show that max-stability of…

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

Deep learning from strongly mixing observations: Sparse-penalized regularization and minimax optimality

William Kengne, Modou Wade

The explicit regularization and optimality of deep neural networks estimators from independent data have made considerable progress recently. The study of such properties on depend…

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…

stat.ML2023★ 1 cited

Penalized deep neural networks estimator with general loss functions under weak dependence

William Kengne, Modou Wade

This paper carries out sparse-penalized deep neural networks predictors for learning weakly dependent processes, with a broad class of loss functions. We deal with a general framew…

stat.ML2023

Sparse-penalized deep neural networks estimator under weak dependence

William Kengne, Modou Wade

We consider the nonparametric regression and the classification problems for -weakly dependent processes. This weak dependence structure is more general than conditions such as,…