Some recent developments in multiparameter eigenvalue problems
We review some recent results in multiparameter eigenvalue problems. This includes the fascinating problem of finding determinantal representations of minimal size. This reflects some work with Bor Plestenjak.
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- Voorwaarden: foundational understanding of artificial intelligence, numerical optimization, and mathematical concepts
- Prijs: free
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TU Eindhoven, the Netherlands
Back to the Roots Seminar Series
The ERC research project "Back to the roots of data-driven dynamical system identification", led by Prof. Dr. Bart De Moor (KU Leuven, ESAT-STADIUS), focuses on system identification, where mathematical models are derived from observed data generated by systems such as medical monitoring, electricity consumption and industrial processes. Utilizing optimization algorithms, one seeks to identify the best model in a chosen model class. This methodology finds widespread application across thousands of use cases within the AI community. However, there is no guarantee that optimization algorithms will find the best model. Present-day optimization practices are heuristic in nature, yielding results that may not be reproducible and consequently difficult to interpret.
The main objective of the Back to the Roots project is to develop a theoretical framework that combines model classes and optimization algorithms, enabling the calculation of the optimal model within the specified model class with 100% certainty.
