Zobrazeno 1 - 10
of 463
pro vyhledávání: '"Termier, A."'
Autor:
Kelodjou, Gwladys, Rozé, Laurence, Masson, Véronique, Galárraga, Luis, Gaudel, Romaric, Tchuente, Maurice, Termier, Alexandre
Publikováno v:
AAAI Conference on Artificial Intelligence, 2024
Machine learning techniques, such as deep learning and ensemble methods, are widely used in various domains due to their ability to handle complex real-world tasks. However, their black-box nature has raised multiple concerns about the fairness, trus
Externí odkaz:
http://arxiv.org/abs/2312.12115
lcensemble is a high-performing, scalable and user-friendly Python package for the general tasks of classification and regression. The package implements Local Cascade Ensemble (LCE), a machine learning method that further enhances the prediction per
Externí odkaz:
http://arxiv.org/abs/2308.07250
Counterfactual explanations have become a mainstay of the XAI field. This particularly intuitive statement allows the user to understand what small but necessary changes would have to be made to a given situation in order to change a model prediction
Externí odkaz:
http://arxiv.org/abs/2304.12943
Publikováno v:
MLmDS 2023 - AAAI Workshop When Machine Learning meets Dynamical Systems: Theory and Applications, Feb 2023, Washington (DC), United States. pp.1-6
To get a good understanding of a dynamical system, it is convenient to have an interpretable and versatile model of it. Timed discrete event systems are a kind of model that respond to these requirements. However, such models can be inferred from tim
Externí odkaz:
http://arxiv.org/abs/2301.05041
Publikováno v:
ECML PKDD 2022 - European Conference on Machine Learning and Knowledge Discovery in Databases., Sep 2022, Grenoble, France
Counterfactual explanation is a common class of methods to make local explanations of machine learning decisions. For a given instance, these methods aim to find the smallest modification of feature values that changes the predicted decision made by
Externí odkaz:
http://arxiv.org/abs/2212.10847
We are interested in understanding the underlying generation process for long sequences of symbolic events. To do so, we propose COSSU, an algorithm to mine small and meaningful sets of sequential rules. The rules are selected using an MDL-inspired c
Externí odkaz:
http://arxiv.org/abs/2109.07519
Autor:
Olivier Gauriau, Luis Galárraga, François Brun, Alexandre Termier, Loïc Davadan, François Joudelat
Publikováno v:
Smart Agricultural Technology, Vol 7, Iss , Pp 100380- (2024)
Crop diseases and pests constitute significant causes of yield losses for crops. To limit the harm incurred by those events, farmers resort to plant protection products. Such products are known to have adverse effects both on the environment and on h
Externí odkaz:
https://doaj.org/article/95d6e5c43b2443c7a681690e2e043dce
Autor:
Gauriau, Olivier, Galárraga, Luis, Brun, François, Termier, Alexandre, Davadan, Loïc, Joudelat, François
Publikováno v:
In Smart Agricultural Technology March 2024 7
Publikováno v:
Proceedings of the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2021)
We introduce HiPaR, a novel pattern-aided regression method for tabular data containing both categorical and numerical attributes. HiPaR mines hybrid rules of the form $p \Rightarrow y = f(X)$ where $p$ is the characterization of a data region and $f
Externí odkaz:
http://arxiv.org/abs/2102.12370
Multivariate Time Series (MTS) classification has gained importance over the past decade with the increase in the number of temporal datasets in multiple domains. The current state-of-the-art MTS classifier is a heavyweight deep learning approach, wh
Externí odkaz:
http://arxiv.org/abs/2009.04796