12 citations · 45 across the 20 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…
biquality-learn: a Python library for Biquality Learning
Pierre Nodet, Vincent Lemaire, Alexis Bondu +1
The democratization of Data Mining has been widely successful thanks in part to powerful and easy-to-use Machine Learning libraries. These libraries have been particularly tailored…
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…