Emilie Devijver

João Paulo Almeida de Mendonça

J. Mach. Learn. Res., 2024

Regression tree-based active learning.

[BibT_eX]

[DOI]

Ashna Jose

Data Min. Knowl. Discov., 2024

Ensembles of Probabilistic Regression Trees.

[BibT_eX]

[DOI]

CoRR, 2024

Classification Tree-based Active Learning: A Wrapper Approach.

[BibT_eX]

[DOI]

CoRR, 2024

On the Fly Detection of Root Causes from Observed Data with Application to IT Systems.

[BibT_eX]

[DOI]

CoRR, 2024

Efficient Initial Data Selection and Labeling for Multi-Class Classification Using Topological Analysis.

[BibT_eX]

[DOI]

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

On the Fly Detection of Root Causes from Observed Data with Application to IT Systems.

[BibT_eX]

[DOI]

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Identifiability of total effects from abstractions of time series causal graphs.

[BibT_eX]

[DOI]

CoRR, 2023

Pool-Based Active Learning with Proper Topological Regions.

[BibT_eX]

[DOI]

CoRR, 2023

Case Studies of Causal Discovery from IT Monitoring Time Series.

[BibT_eX]

[DOI]

Ali Aït-Bachir

Christophe de Bignicourt

CoRR, 2023

Hybrids of Constraint-based and Noise-based Algorithms for Causal Discovery from Time Series.

[BibT_eX]

[DOI]

CoRR, 2023

Survey and Evaluation of Causal Discovery Methods for Time Series (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

Survey and Evaluation of Causal Discovery Methods for Time Series.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2022

A Conditional Mutual Information Estimator for Mixed Data and an Associated Conditional Independence Test.

[BibT_eX]

[DOI]

Entropy, 2022

Entropy-Based Discovery of Summary Causal Graphs in Time Series.

[BibT_eX]

[DOI]

Entropy, 2022

Inferring extended summary causal graphs from observational time series.

[BibT_eX]

[DOI]

CoRR, 2022

Self-Training: A Survey.

[BibT_eX]

[DOI]

CoRR, 2022

Wrapper feature selection with partially labeled data.

[BibT_eX]

[DOI]

Appl. Intell., 2022

Discovery of extended summary graphs in time series.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Multi-class Probabilistic Bounds for Self-learning.

[BibT_eX]

[DOI]

CoRR, 2021

A Mixed Noise and Constraint-Based Approach to Causal Inference in Time Series.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

2020

Prediction regions through Inverse Regression.

[BibT_eX]

[DOI]

Émeline Perthame

J. Mach. Learn. Res., 2020

Smooth And Consistent Probabilistic Regression Trees.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Semi-supervised Wrapper Feature Selection with Imperfect Labels.

[BibT_eX]

[DOI]

CoRR, 2019

Scaling Causal Inference in Additive Noise Models.

[BibT_eX]

[DOI]

Proceedings of the 2019 ACM SIGKDD Workshop on Causal Discovery, 2019

Transductive Bounds for the Multi-Class Majority Vote Classifier.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Dealing with Uncertain Inputs in Regression Trees.

[BibT_eX]

[DOI]

CoRR, 2018

2017

Joint rank and variable selection for parsimonious estimation in a high-dimensional finite mixture regression model.

[BibT_eX]

[DOI]

J. Multivar. Anal., 2017

Model-based regression clustering for high-dimensional data: application to functional data.

[BibT_eX]

[DOI]

Adv. Data Anal. Classif., 2017

2015

Block-diagonal covariance selection for high-dimensional Gaussian graphical models.

[BibT_eX]

[DOI]