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20242026
most citedEarly Classification of Time Series: A Survey and Benchmark

1 citations · 1 across the 8 of their papers we have counts for

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8 papers

cs.LG2026

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…

cs.LG2026

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…

cs.LG2025

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…

cs.LG2025

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…

cs.LG2025

Unsupervised Feature Construction for Anomaly Detection in Time Series -- An Evaluation

Marine Hamon, Vincent Lemaire, Nour Eddine Yassine Nair-Benrekia +2

To detect anomalies with precision and without prior knowledge in time series, is it better to build a detector from the initial temporal representation, or to compute a new (tabul…

cs.LG2024

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…

cs.LG2024★ 1 cited

Early Classification of Time Series: A Survey and Benchmark

Aurélien Renault, Alexis Bondu, Antoine Cornuéjols +1

In many situations, the measurements of a studied phenomenon are provided sequentially, and the prediction of its class needs to be made as early as possible so as not to incur too…

cs.LG2024

Constructing Variables Using Classifiers as an Aid to Regression: An Empirical Assessment

Colin Troisemaine, Vincent Lemaire

This paper proposes a method for the automatic creation of variables (in the case of regression) that complement the information contained in the initial input vector. The method w…