News - Recently updated info
Become a member
Multi-set and multi-way models

Multi-set and multi-way data are collected in diverse scientific areas, like chemistry, metabolomics, signal processing and the social sciences. Multi-set data typically involve multivariate data that are organized in different sets or blocks, which have one mode in common. Such data arise when the observation units involved stem from different groups (i.e., blocks sharing the variable mode), or when multiple sorts of information are collected on the same observation units (i.e; blocks sharing the observation unit mode). Multi-way data require the data to be fully crossed, implying that the observation units are measured in different conditions on the same variables. Multi-set and multi-way models aim at capturing the intricate structure in those data sets, primarily using dimensional and categorical reduction models. These models also have applications in scientific computing, where the dimensional reduction is used to simplify computations.

The specialized team focuses on developments in multi-set and multi-way modeling, including their mathematical basis, algorithms and applications. It aims at stimulating the dialogue between the diverse communities interested in multi-set and multi-way modeling, such as statistics, tensor algebra, chemometrics, and psychometrics.

Eva Ceulemans, Leuven University, Belgium.
Alwin Stegeman, University of Groningen, The Netherlands.
Marieke Timmerman, University of Groningen, The Netherlands.
  1. Evrim Acar, University of Copenhagen, Denmark.
  2. Orly Alter, University of Utah, USA.
  3. Brett W. Bader, DG Labs, USA.
  4. Rasmus Bro, Royal Veterinary \& Agricultural University, Denmark.
  5. Eva Ceulemans, University of Leuven, Belgium.
  6. Eva Ceulemans, University of Leuven, Belgium.
  7. Marina Cocchi, Universita di Modena e Reggio Emilia, Italy.
  8. Pierre Comon, I3S - CNRS, France.
  9. Lieven de Lathauwer, University of Leuven, Belgium.
  10. Paolo Giordani, Sapienza University of Rome, Italy.
  11. Patrick Groenen, Erasmus University Rotterdam, Netherlands.
  12. Mohamed Hanafi, ONIRIS, France.
  13. Mia Hubert, KU Leuven, Belgium.
  14. Francois Husson, Agrocampus Rennes, France.
  15. Heungsun Hwang, McGill University, Canada.
  16. Jeroen Jansen, University of Nijmegen, The Netherlands.
  17. Julie Josse, Agrocampus, France.
  18. Julie Josse, Agrocampus Ouest, France.
  19. Henk Kiers, University of Groningen, Netherlands.
  20. Tamara Kolda, Sandia National Laboratories, USA.
  21. Pieter Kroonenberg, Leiden University, Netherlands.
  22. Dana Lahat, GIPSA-Lab, France.
  23. Michel Meulders, HUBrussel, Belgium.
  24. Morten Morup, DTU Informatics, Denmark.
  25. Tormod Naes, NOFIMA, Norway.
  26. Ndeye Niang, CNAM, France.
  27. Anuradha Roy, The University of Texas at San Antonio, United States.
  28. Nikos Sidiropoulos, University of Minnesota, United States.
  29. Age Smilde, University of Amsterdam, The Netherlands.
  30. Mikael Sorensen, KU Leuven, Belgium.
  31. Alwin Stegeman, University of Groningen, The Netherlands.
  32. Arthur Tenenhaus, CentraleSupelec, France.
  33. Michel Tenenhaus, HEC School of Management, France.
  34. Marieke Timmerman, University of Groningen, Netherlands.
  35. Michel van de Velden, Erasmus University Rotterdam, The Netherlands.
  36. Katrijn Van Deun, KU Leuven, Belgium.
  37. Katrijn Van Deun, Tilburg University, Netherlands.
  38. Iven Van Mechelen, University of Leuven, Belgium.
  39. Donatella Vicari, Sapienza University, Italy.
  40. Tom Frans Wilderjans, Leiden University, Netherlands.