8 citations · 8 across the 9 of their papers we have counts for
16 papers · 1 filter
End-to-end Early Classification of Time Series in Non-Stationary Environments
Aurélien Renault, Alexis Bondu, Antoine Cornuéjols +1
Early Classification of Time Series (ECTS) requires making accurate decisions as early as possible in inherently online and evolving environments. Yet, most existing methods assume…
Early Classification of Time Series in Non-Stationary Cost Regimes
Aurélien Renault, Alexis Bondu, Antoine Cornuéjols +1
Early Classification of Time Series (ECTS) addresses decision-making problems in which predictions must be made as early as possible while maintaining high accuracy. Most existing…
Khiops: An End-to-End, Frugal AutoML and XAI Machine Learning Solution for Large, Multi-Table Databases
Marc Boullé, Nicolas Voisine, Bruno Guerraz +10
Khiops is an open source machine learning tool designed for mining large multi-table databases. Khiops is based on a unique Bayesian approach that has attracted academic interest w…
Alert: Learning Trigger Functions for Early Classification of Time Series using Deep-RL
Aurélien Renault, Alexis Bondu, Antoine Cornuéjols +1
Early Classification of Time Series (ECTS) is vital in fields like industrial monitoring and medical triage, where quick and accurate predictions are essential. One of the core cha…
Mislabeled examples detection viewed as probing machine learning models: concepts, survey and extensive benchmark
Thomas George, Pierre Nodet, Alexis Bondu +1
Mislabeled examples are ubiquitous in real-world machine learning datasets, advocating the development of techniques for automatic detection. We show that most mislabeled detection…
ml_edm package: a Python toolkit for Machine Learning based Early Decision Making
Aurélien Renault, Youssef Achenchabe, Édouard Bertrand +4
\texttt{ml\_edm} is a Python 3 library, designed for early decision making of any learning tasks involving temporal/sequential data. The package is also modular, providing research…