The workshop will take place on 27 and 28 March 2025, in the L016 room at CWI, Sciencepark 123, Amsterdam ...

Polynomial optimization is an exciting new field, which emerged in the last two decades. Building up on cross fertilization between mathematics, theoretical computer science and engineering, it has ...

Centrum Wiskunde & Informatica (CWI) is the national research institute for mathematics and computer science in the Netherlands.

I took one course from the semester program called Masterclass on Machine Learning for Inverse Problems. Right now I live in Paris but I came back in May to participate in the course. It was a two-day ...

The study of partition functions and related topics is an active area of research that is at the intersection of combinatorics, probability, theoretical computer science, and statistical physics.

Centrum Wiskunde & Informatica (CWI) is the national research institute for mathematics and computer science in the Netherlands.

Today (22 January) marks the final day of this systems-focused conference, which emphasizes a systems architecture perspective and attracts practitioners from both academia and industry. Among the ...

Which element/part of the semester program did you participate in? I participated in all the events of the Research Program on Polynomial Optimization and Applications, which consisted of 3 workshops ...

Machine Learning is a key enabler of advances in science, industry and society. In fact, machine learning methods touch nearly all aspects of our physical and online experience. As such, the design ...

Data-driven methods for inverse problems Our Computational Imaging research group (CI) kicked off the Research Semester Programme with a series of events about Data-driven methods for inverse problems ...

In the first half of 2026, the following team of researchers will organize the Semester Programme "Democratising Real-World Problem Tailored Optimisation": Vanessa Volz (CWI), Anton Bouter (CWI), ...

This semester programme aims to combine optimization and machine learning, in order to develop data-centric methods attaining both performance guarantees and explainability. This includes the design ...