MLVis 2022
Machine Learning Methods in Visualisation for Big Data 2022
13 June 2022, Co-located with EuroVis 2022, Rome, Italy
Machine Learning Methods in Visualisation will be held as part of EuroVis 2022 in Rome, Italy. The seventh edition of this co-located event will be part-tutorial and part-workshop so as to increase the interaction between researchers.
Part of the MLVis 2022 programme will consist of short papers.
We solicit short papers on machine learning methods in visualisation from both the machine learning and visualisation communities, addressing how the two technologies can be used together to provide greater insight to end users.
Topics include but are not limited to: Explainable Machine Learning, Dimensionality Reduction, Visualisation of Clustering, Regression, and Classification, Steerable Machine Learning, Visualisation to Improve Machine Learning Models, Automation of Visualisation and Visual Analytics, Visualisation and Machine Learning in Text Analytics, Visualisation in Online Machine Learning
Important Dates
- Submission deadline (extended): April 20, 2022
- Notification deadline: May 6, 2022
- Camera-ready deadline: May 13, 2022
All submission deadlines are at 23:59 Anywhere on Earth on the date indicated.
Submission Guidelines
Paper submissions for MLVis should be at most 4 pages in the MLVis 2022 LaTeX style, with an additional page allowed for references. All submissions must be original works that have not been published previously in any conference proceedings, magazine, journal, or edited book. Papers are to be submitted via the new PCS at: https://new.precisionconference.com/ (when making your submission, choose society “Eurographics”, conference/journal “MLVis” and track “MLVis 2022 workshop”, then click “Go”). The submissions do not need to be blind.
Publication
At least one author of an accepted paper must register and participate in the MLVis 2022 workshop to present the accepted work.
Proceedings will be published by the Eurographics Association, and be stored on the Eurographics Digital Library.
Programme
The workshop takes place at the Angelicum Conference Center. Both sessions are held in the room Aula Minor.
Part 1 (9:00-10:40, room: Aula Minor, chair: Daniel Archambault)
- 9:00-9:10 Introduction to MLVis
- 9:10-9:45 Machine Learning and Visualisation for Time Series Data
Speaker: Ian Nabney - 9:45-10:20 Statistical Machine Learning for Text Data
Speaker: Jaakko Peltonen - 10:20-10:40 Visualisation of Text and Network Data from the Bloggosphere
Speaker: Daniel Archambault
Part 2 (11:10-12:50, room: Aula Minor, chair: Ian Nabney)
- 11:10-11:30 Visual Exploration of Neural Network Projection Stability
Carlo Bredius, Zonglin Tian, and Alexandru Telea - 11:30-11:50 Saliency Clouds: Visual Analysis of Point Cloud-oriented Deep Neural Networks in DeepRL for Particle Physics
Raju Ningappa Mulawade, Christoph Garth, and Alexander Wiebel - 11:50-12:10 ViNNPruner: Visual Interactive Pruning for Deep Learning
Udo Schlegel, Samuel Schiegg, and Daniel Keim - 12:10-12:40 Panel
- 12:40-12:50 Closing
Organising Committee
- Daniel Archambault (Swansea University, United Kingdom)
- Ian Nabney (University of Bristol, United Kingdom)
- Jaakko Peltonen (Tampere University, Finland)
International Program Committee
- Benjamin Bach (University of Edinburgh, United Kingdom)
- Barbara Hammer (Bielefeld University, Germany)
- Nick Holliman (King’s College London, United Kingdom)
- John A. Lee (Universite catholiqué de Louvain, Belgium)
- Mike Tipping (University of Bath, United Kingdom)
- Michel Verleysen (Université catholique de Louvain, Belgium)
- Yong Wang (Singapore Management University, Singapore)