Connectionists: Interaction and User Integration in ML for Infovis at ESANN'18

[Benoit Frenay]

[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


DESCRIPTION:

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
  *      scalability
  *      applications in industry, agriculture, medicine, biology, etc.


SUBMISSION:


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.


IMPORTANT DATES:


Paper submission deadline : 20 November 2017

Notification of acceptance : 31 January 2018

The ESANN 2014 conference : 25-27 April 2018


SPECIAL SESSION ORGANISERS:


Prof. Bruno Dumas

Université de Namur, Belgium

E-mail: bruno.dumas at unamur.be

Website: 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

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

Website:<http://bfrenay.wordpress.com/>https://mlg.info.ucl.ac.be/Members/JohnLee

Phone: +32 2 764 95 28


-- 

Benoît FRÉNAY
Associate Professor
Faculty of Computer Science

T. +32 (0)81 724 976 (secr. 725 252)
F. +32 (0)81 724 967
benoit.frenay at unamur.be <mailto:benoit.frenay at unamur.be>

Université de Namur ASBL
Rue de Bruxelles 61 - 5000 Namur

Let’s respect the environment together.
Only print this message if necessary!

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20171006/5cbd204d/attachment.html>