[Infovis] Interaction and User Integration in ML for Infovis at ESANN'18

Bruno Dumas bruno.dumas at unamur.be
Wed Aug 30 09:53:56 CEST 2017

[Apologies if you receive multiple copies of this CFP]

Call for papers:  special session on "Interaction and User Integration in Machine Learning for Information Visualisation" at ESANN 2018

European Symposium on Artificial Neural Networks, Computational Intelligence and

Machine Learning (ESANN 2018). 25-27 April 2018, Bruges, Belgium - http://www.esann.org <http://www.esann.org/>


Many methods have been developed in machine learning (ML) for information visualisation (infovis).  For example, PCA, MDS, t-SNE and improvements are standard tools to reduce the dimensionality of high dimensional datasets for visualisation purposes.  However, multiple other means are regularly used in the field of infovis when tackling datasets with high dimensionality.  Letting the user manipulate the visualisation is one of these means, either through selection, navigation or filtering.  Introducing manipulation of the visualisation also integrates the user as a core aspect of a given system.  In the context of machine learning, beyond the informational and exploratory use of infovis, users' feedback can for example be highly informational to drive the dimensionality reduction process.

This special session of the ESANN conference is a followup of the special session on "Information Visualisation and Machine Learning: Techniques, Validation and Integration" at ESANN 2016.  It aims to gather researchers that integrate users in the core of ML methods for infovis.  New algorithms and frameworks are welcome, as well as experimental use cases that bring new insight in the integration of interaction and user integration in ML for infovis. This special session aims to provide practitioners from both communities a common forum of discussion where issues at the crossroads of machine learning and information visualisation could be discussed.

Topics of interest include, but are not limited to:

       supervised and semi-supervised machine learning and infovis
       unsupervised ML (clustering, dimension reduction)
       user feedback on metaparameters
       new visual paradigms for machine learning
       interaction techniques for infovis with/of machine learning
       user and device adaptivity for visual analytics
       warm restart and dedicated optimization techniques
       applications in industry, agriculture, medicine, biology, etc.


Prospective authors must submit their paper through the ESANN portal following the instructions provided in http://www.elen.ucl.ac.be/esann/index.php?pg=submission <http://www.elen.ucl.ac.be/esann/index.php?pg=submission>.  Each paper will undergo a peer reviewing process for its acceptance.  Authors should send as soon as possible an e-mail with the tentative title of their contribution to the special session organisers.


Paper submission deadline : 20 November 2017
Notification of acceptance : 31 January 2018
The ESANN 2014 conference : 25-27 April 2018


Prof. Bruno Dumas
Université de Namur, Belgium
E-mail: bruno.dumas at unamur.be <mailto:bruno.dumas at unamur.be>
Website: http://directory.unamur.be/staff/bdumas <http://directory.unamur.be/staff/bdumas>
Phone: +32 81 72 49 75

Prof. Benoît Frénay
Université de Namur, Belgium
E-mail: benoit.frenay at unamur.be <mailto:benoit.frenay at unamur.be>
Website: http://bfrenay.wordpress.com <http://bfrenay.wordpress.com/>
Phone: +32 81 72 49 76

Prof. John Lee
Université catholique de Louvain, Belgium
E-mail: john.lee at uclouvain.be <mailto:john.lee at uclouvain.be>
Website: https://mlg.info.ucl.ac.be/Members/JohnLee <https://mlg.info.ucl.ac.be/Members/JohnLee>
Phone: +32 2 764 95 28

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