CORDIS Project
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This project aims to improve the modeling of complex nonlinear processes by transitioning from linear to polynomial models. It focuses on developing robust numerical methods to solve large polynomial systems, which are crucial for various applications in fields like machine learning and bioinformatics.
The modelling of real-life nonlinear processes is commonly done via local linearization, i.e., by fitting linear models to small ranges of the process.
Linearization is, however, quite limited in range and model properties. A foundational step is currently being made by moving from linear to multi-linear or polynomial models to capture more general features of a nonlinear process over larger ranges. A second important development is Big Data: nowadays we often encounter high-dimensional dataset…
KATHOLIEKE UNIVERSITEIT LEUVEN
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