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20232026
most citedExcess risk bound for deep learning under weak dependence

2 citations · 3 across the 9 of their papers we have counts for

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stat.ML2026

Adaptive deep nonparametric regression from dependent data under covariate shift

William Kengne, Ehud Mossa Ockegna

Covariate shift often occurs because, in many real applications, the source and the target observations may be generated from different distributions. In this case, the standard me…

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.…