Rebecca Marion

According to our database, Rebecca Marion authored at least 9 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Gradient-based explanation for non-linear non-parametric dimensionality reduction.

Sacha Corbugy, Rebecca Marion, Benoît Frénay

Data Min. Knowl. Discov., November, 2024

Improving the Feature Selection Stability of the Delta Test in Regression.

Rebecca Marion, Benoît Frénay

IEEE Trans. Artif. Intell., May, 2024

2022

VC-PCR: A Prediction Method based on Supervised Variable Selection and Clustering.

Rebecca Marion, Johannes Lederer, Bernadette Govaerts, Rainer von Sachs

CoRR, 2022

Globally local and fast explanations of t-SNE-like nonlinear embeddings.

Pierre Lambert, Rebecca Marion, Julien Albert, Emmanuel Jean, Sacha Corbugy, Cyril de Bodt

Proceedings of the CIKM 2022 Workshops co-located with 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), 2022

2021

Statistical and machine learning methods for identifying clusters of variables: with applications in omics, ecology and psychology.

Rebecca Marion

PhD thesis, 2021

BIOT: Explaining multidimensional nonlinear MDS embeddings using the Best Interpretable Orthogonal Transformation.

Adrien Bibal, Rebecca Marion, Rainer von Sachs, Benoît Frénay

Neurocomputing, 2021

2020

Comparison of Cluster Validity Indices and Decision Rules for Different Degrees of Cluster Separation.

Sara Kaczynska, Rebecca Marion, Rainer von Sachs

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019

BIR: A method for selecting the best interpretable multidimensional scaling rotation using external variables.

Rebecca Marion, Adrien Bibal, Benoît Frénay

Neurocomputing, 2019

2018

Finding the most interpretable MDS rotation for sparse linear models based on external features.

Adrien Bibal, Rebecca Marion, Benoît Frénay

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018