Call for papers


Special Session on

Machine learning and decision making under weakly structured information



at the

11th International Conference on Soft Methods in Probability and Statistics 
(SMPS 2024)

Salzburg (Austria), September 4-6, 2024



Session topic and goal

This session deals with machine learning problems that appear under weak 
information structures and, therefore, fail to be handled by traditional 
methods. The reason for the weak structure can be manifold, ranging from 
complex data and non-typical scales of measurement to generalized uncertainty 
models such as imprecise probabilities. In particular, the topics of the 
session include (but are not limited to):



  *      Imprecise probabilities in ML and statistics
  *      Preferences in ML and statistics
  *      Decision theoretic approaches in ML and statistics
  *      Formal concept analysis in ML and statistics
  *      Non-standard data (e.g. ordinal data, mixed-scaled data)
  *      (Generalized) Bayesian methods in ML and statistics
  *      Uncertainty quantification in ML and statistics
  *      Robustness in decision theory
  *      Robust statistics



Dates

Paper submission deadline: February 29, 2024

Author notification: April 21, 2024

Conference: September 4-6, 2024



Submissions

When submitting the paper, choose the session

Machine learning and decision making under weakly structured information

in the conference management tool. Papers should be 6-8 pages.

All required information can be found on the conference homepage 
https://nam04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.smps2024.com%2F&data=05%7C02%7Cuai%40engr.orst.edu%7C1181705156674687b76708dc28770b59%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638429738966015103%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=rZ9ALetFTTqRd4VeJkY1xeyjmcvfUBHWS9gzKCrpPf0%3D&reserved=0<https://nam04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.smps2024.com%2F&data=05%7C02%7Cuai%40engr.orst.edu%7C1181705156674687b76708dc28770b59%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638429738966015103%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=rZ9ALetFTTqRd4VeJkY1xeyjmcvfUBHWS9gzKCrpPf0%3D&reserved=0>.



Organizers

Please let us know if you plan to submit a contribution to this session as soon 
as possible. Questions or comments can be addressed to:


Thomas Augustin, Christoph Jansen, Georg Schollmeyer

Ludwig-Maximilians-Universität München (Germany)

{thomas.augustin,christoph.jansen,georg.schollmeyer}@stat.uni-muenchen.de


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