Synergies in numerical linear algebra and machine learning
Sept-Nov 2025
An explosion in computing power and the availability of data have driven the rapid development, and widespread adoption, of data science and machine learning (ML). To fully realize the potential of these tools, numerical linear algebra (NLA) has a pivotal role to play. Conversely, novel ML techniques have the potential of improving classical NLA methods, addressing long-standing open mathematical and computational problems.
The upcoming CWI semester program in autumn 2025, themed "Synergies in numerical linear algebra and machine learning", will comprise an autumn school and workshop with industry day, organised by a team including Victorita Dolean (TU/e), Alexander Heinlein (TU Delft), Tristan van Leeuwen (CWI), Benjamin Sanderse (CWI), and Jemima Tabeart (TU/e).
* Autumn school: 27 - 31 October
* Workshop: 1 - 3 December
