429 citations · 633 across the 15 of their papers we have counts for
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cs.LG2019
Sobolev Independence Criterion
Youssef Mroueh, Tom Sercu, Mattia Rigotti +2
We propose the Sobolev Independence Criterion (SIC), an interpretable dependency measure between a high dimensional random variable X and a response variable Y . SIC decomposes to…
eess.AS2019
Multi-Frame Cross-Entropy Training for Convolutional Neural Networks in Speech Recognition
Tom Sercu, Neil Mallinar
We introduce Multi-Frame Cross-Entropy training (MFCE) for convolutional neural network acoustic models. Recognizing that similar to RNNs, CNNs are in nature sequence models that t…
cs.LG2019★ 15 cited
Wasserstein Barycenter Model Ensembling
Pierre Dognin, Igor Melnyk, Youssef Mroueh +3
In this paper we propose to perform model ensembling in a multiclass or a multilabel learning setting using Wasserstein (W.) barycenters. Optimal transport metrics, such as the Was…