Machine Learning Methods in Visualisation for Big Data 2024
Permanent URI for this collection
MLVis 2024 colocated with EuroVis 2024 - 26th EG Conference on Visualization
Odense, Denmark | May 27, 2024
Odense, Denmark | May 27, 2024
Papers
Visualizing Riemannian data with Rie-SNE
[full paper
]
[meta data ]
Introducing Fairness in Graph Visualization via Gradient Descent
[full paper
]
[meta data ]
DimVis: Interpreting Visual Clusters in Dimensionality Reduction With Explainable Boosting
Machine
[full paper
]
[meta data ]
User-Adaptive Visualizations: An Exploration with GPT-4
[full paper
]
[meta data ]
Exploration of Preference Models using Visual Analytics
[full paper
]
[meta data ]
BibTeX (Machine Learning Methods in Visualisation for Big Data 2024)
@inproceedings{10.2312:mlvis.20242011,booktitle = {Machine Learning Methods in Visualisation for Big Data},editor = {Archambault, DanielandNabney, IanandPeltonen, Jaakko}, title = {{MLVis 2024: Frontmatter}},author = {Archambault, DanielandNabney, IanandPeltonen, Jaakko}, year = {2024},publisher = {The Eurographics Association},ISBN = {978-3-03868-256-1},DOI = {10.2312/mlvis.20242011}}
@inproceedings{10.2312:mlvis.20241123,booktitle = {Machine Learning Methods in Visualisation for Big Data},editor = {Archambault, DanielandNabney, IanandPeltonen, Jaakko}, title = {{Visualizing Riemannian data with Rie-SNE}},author = {Bergsson, AndriandHauberg, Søren}, year = {2024},publisher = {The Eurographics Association},ISBN = {978-3-03868-256-1},DOI = {10.2312/mlvis.20241123}}
@inproceedings{10.2312:mlvis.20241124,booktitle = {Machine Learning Methods in Visualisation for Big Data},editor = {Archambault, DanielandNabney, IanandPeltonen, Jaakko}, title = {{Introducing Fairness in Graph Visualization via Gradient Descent}},author = {Hong, Seok-HeeandLiotta, GiuseppeandMontecchiani, FabrizioandNöllenburg, MartinandPiselli, Tommaso}, year = {2024},publisher = {The Eurographics Association},ISBN = {978-3-03868-256-1},DOI = {10.2312/mlvis.20241124}}
@inproceedings{10.2312:mlvis.20241125,booktitle = {Machine Learning Methods in Visualisation for Big Data},editor = {Archambault, DanielandNabney, IanandPeltonen, Jaakko}, title = {{DimVis: Interpreting Visual Clusters in Dimensionality Reduction With Explainable Boosting Machine}},author = {SALMANIAN, PARISAandChatzimparmpas, AngelosandKaraca, Ali CanandMartins, Rafael M.}, year = {2024},publisher = {The Eurographics Association},ISBN = {978-3-03868-256-1},DOI = {10.2312/mlvis.20241125}}
@inproceedings{10.2312:mlvis.20241126,booktitle = {Machine Learning Methods in Visualisation for Big Data},editor = {Archambault, DanielandNabney, IanandPeltonen, Jaakko}, title = {{User-Adaptive Visualizations: An Exploration with GPT-4}},author = {Yanez, FernandoandNobre, Carolina}, year = {2024},publisher = {The Eurographics Association},ISBN = {978-3-03868-256-1},DOI = {10.2312/mlvis.20241126}}
@inproceedings{10.2312:mlvis.20241127,booktitle = {Machine Learning Methods in Visualisation for Big Data},editor = {Archambault, DanielandNabney, IanandPeltonen, Jaakko}, title = {{Exploration of Preference Models using Visual Analytics}},author = {Buchmüller, RaphaelandZymla, Mark-MatthiasandKeim, DanielandButt, MiriamandSevastjanova, Rita}, year = {2024},publisher = {The Eurographics Association},ISBN = {978-3-03868-256-1},DOI = {10.2312/mlvis.20241127}}