3 citations · 4 across the 5 of their papers we have counts for
5 papers
MCD: Marginal Contrastive Discrimination for conditional density estimation
Katia Meziani, Aminata Ndiaye, Benjamin Riu
We consider the problem of conditional density estimation, which is a major topic of interest in the fields of statistical and machine learning. Our method, called Marginal Contras…
AdaCap: Adaptive Capacity control for Feed-Forward Neural Networks
Katia Meziani, Karim Lounici, Benjamin Riu
The capacity of a ML model refers to the range of functions this model can approximate. It impacts both the complexity of the patterns a model can learn but also memorization, the…
Muddling Label Regularization: Deep Learning for Tabular Datasets
Karim Lounici, Katia Meziani, Benjamin Riu
Deep Learning (DL) is considered the state-of-the-art in computer vision, speech recognition and natural language processing. Until recently, it was also widely accepted that DL is…
Muddling Labels for Regularization, a novel approach to generalization
Karim Lounici, Katia Meziani, Benjamin Riu
Generalization is a central problem in Machine Learning. Indeed most prediction methods require careful calibration of hyperparameters usually carried out on a hold-out \textit{val…
Optimizing generalization on the train set: a novel gradient-based framework to train parameters and hyperparameters simultaneously
Karim Lounici, Katia Meziani, Benjamin Riu
Generalization is a central problem in Machine Learning. Most prediction methods require careful calibration of hyperparameters carried out on a hold-out \textit{validation} datase…