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<h1 class="title">Vis&ML for XAI - Special Session of ICPRAI
2022<br>
</h1>
<h1 class="title"><font size="2">Bridging the Gap between ML and
Visualization communities for eXplainable Artificial
Intelligence</font></h1>
<p class="subtitle"><br>
</p>
</header>
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<td valign="middle" align="center"><a
href="https://bgmv-xai.labri.fr/"><img id="header_logo"
style="margin-right: 15px;"
src="https://bgmv-xai.labri.fr/imgs/paris_rectangle_400_200.jpg"
alt="" name="header_logo"></a></td>
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<div id="header_title"><a style="color: #000000;"
href="https://icprai2022.sciencesconf.org/">ICPRAI 2022
- 3rd International Conference on Pattern Recognition
and Artificial Intelligence<br>
<br>
</a></div>
<div id="header_subtitle">June 1-<sup> </sup>3, 2022<br>
Doctoral consortium: May 31, 2022</div>
<div> </div>
<div id="header_subtitle"><a
href="https://icprai2022.sciencesconf.org/">Paris
(France)</a></div>
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<h1 id="call-for-paper">Call for paper</h1>
<h2 id="about">About</h2>
<p>The rise of machine learning approaches, and in particular deep
learning, has led to a significant increase in the performance of
AI systems. However, it has also raised the question of the
reliability and explicability of their predictions for
decision-making (<em>i.e.</em>, the black-box issue of the deep
models). Such shortcomings also raise many ethical and political
concerns that prevent wider adoption of this potentially highly
beneficial technology, especially in critical areas, such as
healthcare, self-driving cars or security. It is therefore
critical to understand how their predictions correlate with
information perception and expert decision-making. The objective
of eXplainable AI (XAI) is to open this black-box by proposing
methods to understand and explain how these systems produce their
decisions.</p>
<p>Research work in XAI is currently carried out in parallel by the
Machine Learning and the Information Visualization communities
using methodologies and competencies from their own field. This
special session hosted by the <a
href="https://icprai2022.sciencesconf.org/">ICPRAI conference</a>,
endorsed by IAPR, is an opportunity to fill the gap between
Machine Learning and Information Visualization communities and to
promote new joint research paths.</p>
<h2 id="topics">Topics</h2>
<p>Here are the main, but not limited to, topics of interest:</p>
<ul>
<li>Trust, Uncertainty, Fairness, Accountability and Transparency</li>
<li>Explainable/Interpretable Machine Learning</li>
<li>Information visualization for models or their predictions</li>
<li>Interactive applications for XAI</li>
<li>XAI Evaluation and Benchmarks</li>
<li>Human-AI interface and interaction design</li>
<li>Sample-centric and Dataset-centric explanations</li>
<li>Attention mechanisms for XAI</li>
<li>Pruning with XAI</li>
</ul>
<p>We expect papers written by researchers from both communities,
with a preference for works that imply a joint research (e.g.,
visualization experts with machine learning experts). Paper
selection will be achieved by a program committee of experts in
Machine Learning and experts in Information Visualization;
additionally, each paper will be reviewed by at least one expert
of the two communities.</p>
<h1 id="program-comittee">Program Comittee</h1>
<ul>
<li>David Auber, France, Univ. Bordeaux / LaBRI</li>
<li>Thomas Baltzer Moeslund, Denmark, Aalborg University / Visual
Analysis and Perception Laboratory</li>
<li>Alexandre Benoit, France, University Savoie Mont Blanc /
LISTIC</li>
<li>Jenny Benois-Pineau, France, Univ. Bordeaux / LaBRI</li>
<li>Romain Bourqui, France, Univ. Bordeaux / LaBRI</li>
<li>André CPLF de Carvalho, Brazil, University of Sao Paulo / ICMC<br>
</li>
<li>Romain Giot, France, Univ. Bordeaux / LaBRI</li>
<li>Christophe Hurter, France, Ecole Nationale de l’Aviation
Civile</li>
<li>Mark Keane, Ireland, UCD Dublin / Insight SFI Centre for Data
Analytics</li>
<li>Stefanos Kollias, Greece, National Technical University of
Athens / Image, Video and Multimedia Systems Lab</li>
<li>Sebastian Lapuschkin, Germany, Fraunhofer Institute for
Telecommunications</li>
<li>Grégoire Montavon, Germany, Universität Berlin<br>
</li>
<li>Harold Mouchere, France, Université de Nantes / LS2N<br>
</li>
<li>Luis Gustavo Nonato, Brazil, University of São Paulo /
Instituto de Ciencias Matematicas e de Computacao</li>
<li>Dragutin Petkovic, USA, San Francisco State University</li>
<li>Wojciech Samek, Germany, Fraunhofer Heinrich Hertz Institute</li>
<li>Nicolas Thome, France, CNAM/Cedric<br>
</li>
<li>Alex Telea, Nederland, Utrecht University / Department of
Information and Computing Sciences</li>
<li>Romain Vuillemot, France, ENS Lyon / LIRIS</li>
</ul>
<h1 id="paper-submission">Paper submission</h1>
<p>A paper can be submitted via the EasyChair online submission
system at the following address: <a
href="https://easychair.org/my/conference?conf=icprai2022"
class="uri moz-txt-link-freetext">https://easychair.org/my/conference?conf=icprai2022</a>.
You must select the item <em>ICPRAI 2022 - SS - Vis&ML for
XAI: Bridging the gap between machine learning and visualization
communities for eXplainable Artificial Intelligence</em>.</p>
<h1 id="paper-guidelines">Paper guidelines</h1>
<p>Articles should be prepared according to the <a
href="https://www.springer.com/fr/computer-science/lncs/conference-proceedings-guidelines">LNCS
author guidelines</a> and <a
href="https://resource-cms.springernature.com/springer-cms/rest/v1/content/19238648/data/v1">templates</a>
and they should be at most twelve pages long. All papers must be
submitted in electronic format as PDF files before the submission
deadline.</p>
<p>All papers are subject to a single-blind review process.</p>
<p>Accepted papers will be presented at the conference and will be
published by <a href="http://www.springer.com/">Springer</a> in
the <a href="http://www.springer.com/gp/computer-science/lncs">Lecture
Notes in Computer Science</a>. Before publication, the authors
will be requested to fill and sign Springer’s form for the consent
to publish and the copyright transfer.</p>
<p>Keep in mind that papers that do not meet the guidelines will be
returned to the authors. The articles will be allowed to go
through the reviewing process only if they satisfy the specified
requirements.</p>
<h1 id="important-dates">Important dates</h1>
<ul>
<li><code>15/12/2021</code>: Submission deadline</li>
<li><code>08/03/2022</code>: Author notification</li>
<li><code>22/03/2022</code>: Camera ready deadline</li>
<li><code>01/06/2022--03/06/2022</code>: ICPRAI 2022 - 3rd
International Conference on Pattern Recognition and Artificial
Intelligence</li>
</ul>
<h1 id="special-session-organizes">Special Session organizes</h1>
<ul>
<li><a href="mailto:romain.bourqui+icprai@u-bordeaux.fr">Romain
Bourqui, France, Univ. Bordeaux / LaBRI</a></li>
<li><a href="mailto:romain.giot+icprai@u-bordeaux.fr">Romain Giot,
France, Univ. Bordeaux / LaBRI</a></li>
<li><a href="mailto:wojciech.samek+icprai@hhi.fraunhofer.de">Wojciech
Samek, Germany, Fraunhofer Heinrich Hertz Institute</a></li>
</ul>
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