Scheduled presentations:

• Clustered Federated Learning Through Consensus-based Optimization
  J. Carrillo (University of Oxford), S. Li (University Of Wisconsin-Madison), N. Trillos (University of Wisconsin-Madison), *Y. Zhu (University of California, Los Angeles)
• Consensus-Based Rare Event Estimation
  K. Althaus (Technical University of Munich), *I. Papaioannou (Technical University of Munich), E. Ullmann (Technical University of Munich)
• Mean-field limits for Consensus-Based Optimization and Sampling
  N. Gerber (Hausdorff Center for Mathematics), F. Hoffmann (Caltech), *U. Vaes (Inria Paris)
• Theoretical Insights of Practical Interest for Consensus-Based Optimization
  *K. Riedl (Technical University of Munich)
• Multiobjective optimization via filtering methods
  *E. Iacomini (University of Ferrara), M. Herty (RWTH Aachen)
• Kinetic Description and Convergence Analysis of Genetic Algorithms for Global Optimization
  *G. Borghi (RWTH Aachen University), L. Pareschi (Heriot-Watt University)