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07/28/2023
Case Studies of Causal Discovery from IT Monitoring Time Series
Information technology (IT) systems are vital for modern businesses, han...
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06/14/2023
Hybrids of Constraint-based and Noise-based Algorithms for Causal Discovery from Time Series
Constraint-based and noise-based methods have been proposed to discover ...
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03/19/2023
Mixture of segmentation for heterogeneous functional data
In this paper we consider functional data with heterogeneity in time and...
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05/19/2022
Inferring extended summary causal graphs from observational time series
This study addresses the problem of learning an extended summary causal ...
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02/24/2022
Self-Training: A Survey
In recent years, semi-supervised algorithms have received a lot of inter...
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09/29/2021
Multi-class Probabilistic Bounds for Self-learning
Self-learning is a classical approach for learning with both labeled and...
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05/21/2021
Entropy-based Discovery of Summary Causal Graphs in Time Series
We address in this study the problem of learning a summary causal graph ...
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11/12/2019
Semi-supervised Wrapper Feature Selection with Imperfect Labels
In this paper, we propose a new wrapper approach for semi-supervised fea...
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10/27/2018
Dealing with Uncertain Inputs in Regression Trees
Tree-based ensemble methods, as Random Forests and Gradient Boosted Tree...
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07/09/2018
Prediction regions through Inverse Regression
Predict a new response from a covariate is a challenging task in regress...
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01/26/2017
Nonlinear network-based quantitative trait prediction from transcriptomic data
Quantitatively predicting phenotype variables by the expression changes ...
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11/12/2015