216 citations · 249 across the 3 of their papers we have counts for
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Non-asymptotic model selection in block-diagonal mixture of polynomial experts models
TrungTin Nguyen, Faicel Chamroukhi, Hien Duy Nguyen +1
Model selection, via penalized likelihood type criteria, is a standard task in many statistical inference and machine learning problems. Progress has led to deriving criteria with…
A non-asymptotic approach for model selection via penalization in high-dimensional mixture of experts models
TrungTin Nguyen, Hien Duy Nguyen, Faicel Chamroukhi +1
Mixture of experts (MoE) are a popular class of statistical and machine learning models that have gained attention over the years due to their flexibility and efficiency. In this w…
Leveraging 3D Information in Unsupervised Brain MRI Segmentation
Benjamin Lambert, Maxime Louis, Senan Doyle +3
Automatic segmentation of brain abnormalities is challenging, as they vary considerably from one pathology to another. Current methods are supervised and require numerous annotated…