8 citations · 8 across the 3 of their papers we have counts for
3 papers · 1 filter
Biquality Learning: a Framework to Design Algorithms Dealing with Closed-Set Distribution Shifts
Pierre Nodet, Vincent Lemaire, Alexis Bondu +1
Training machine learning models from data with weak supervision and dataset shifts is still challenging. Designing algorithms when these two situations arise has not been explored…
Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion
Aurélien Renault, Alexis Bondu, Vincent Lemaire +1
Time Series Classification (TSC) has received much attention in the past two decades and is still a crucial and challenging problem in data science and knowledge engineering. Indee…
An Efficient Shapley Value Computation for the Naive Bayes Classifier
Vincent Lemaire, Fabrice Clérot, Marc Boullé
Variable selection or importance measurement of input variables to a machine learning model has become the focus of much research. It is no longer enough to have a good model, one…