[Ieee_vis] [Deadline extended] Vis & ML for XAI Special Session of ICPRAI 2022

[Romain Bourqui]

[Apologies if you receive multiple copies of this CFP]

Dear all,

ICPRAI conference has delayed the submission date of its paper to the 
_15th of january 2022_,  this also applies for the special session 
"BGMV-XAI 2022 : Vis&ML for XAI - Bridging the Gap between ML and 
Visualization communities for eXplainable Artificial Intelligence".

Please find enclosed the updated CFP.

Best regards

Romain Bourqui, Romain Giot, Wojciech Samek

---


  Vis&ML for XAI - Special Session of ICPRAI 2022


  Bridging the Gap between ML and Visualization communities for
  eXplainable Artificial Intelligence


<https://bgmv-xai.labri.fr/> 	
ICPRAI 2022 - 3rd International Conference on Pattern Recognition and 
Artificial Intelligence

<https://icprai2022.sciencesconf.org/>
June 1-^3, 2022
Doctoral consortium: May 31, 2022
Paris (France) <https://icprai2022.sciencesconf.org/>


  Call for paper


    About

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 (/i.e./, 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.

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 ICPRAI conference 
<https://icprai2022.sciencesconf.org/>, endorsed by IAPR, is an 
opportunity to fill the gap between Machine Learning and Information 
Visualization communities and to promote new joint research paths.


    Topics

Here are the main, but not limited to, topics of interest:

  * Trust, Uncertainty, Fairness, Accountability and Transparency
  * Explainable/Interpretable Machine Learning
  * Information visualization for models or their predictions
  * Interactive applications for XAI
  * XAI Evaluation and Benchmarks
  * Human-AI interface and interaction design
  * Sample-centric and Dataset-centric explanations
  * Attention mechanisms for XAI
  * Pruning with XAI

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.


  Paper submission

A paper can be submitted via the EasyChair online submission system at 
the following address: 
https://easychair.org/my/conference?conf=icprai2022 
<https://easychair.org/my/conference?conf=icprai2022>. You must select 
the item /ICPRAI 2022 - SS - Vis&ML for XAI: Bridging the gap between 
machine learning and visualization communities for eXplainable 
Artificial Intelligence/.


  Important dates

  * *|15/01/2022|**: Submission deadline (revised deadline)*
  * |08/03/2022|: Author notification
  * |22/03/2022|: Camera ready deadline
  * |01/06/2022--03/06/2022|: ICPRAI 2022 - 3rd International Conference
    on Pattern Recognition and Artificial Intelligence


More information is available at: https://bgmv-xai.labri.fr/
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