Overview Research Semester Programme Machine Learning Theory

The programme is centred around presenting open problems and initiating making progress.

Research Semester Programme Machine Learning Theory logo

What is Machine Learning Theory

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 and analysis of these methods if of deep interest. This research semester programme is focused on understanding machine learning through the lens of mathematics and computer science, including especially statistics, combinatorics, convex analysis, game theory and algorithms. The programme consists of a series of events highlighting theoretical aspects of machine learning. It is designed to bring young researchers up to speed, stimulate interaction between researchers, and present and especially attempt to solve open problems.

Focus Topics

  • Statistical and computational learning
  • Online learning and decision-making
  • Active, interactive and reinforcement learning, planning and control
  • Theory of artificial neural networks and robustness
  • Algebraic, Combinatorial, Geometric, Topological and Manifold learning
  • Optimization and Game theory
  • Privacy, Fairness, Resource constraints
  • High-dimensional and non-parametric statistics
  • Adaptive data analysis and selective inference
  • Causality

Aim of the programme

This program aims to bring together researchers from the Netherlands and beyond, with an interest on mathematical and computational aspects of learning. We invite all researchers, especially PhD students and postdoctoral researchers who are working in related topics, to join our events.

Overview events

The Machine Learning Theory semester programme starts with a boot camp to provide a solid foundation for all participants, it runs in Spring 2023.

  • A two-day boot camp is intended for PhD students in ML theory. We will have one and half days of tutorials by researchers, one afternoon of lectures by international keynote speakers, a poster session, a joint dinner, and plenty of time for interaction.
  • The general theme of the afternoon is "The Nature of Information and its Active Acquisition". Our two distinguished speakers will illuminate philosophical and technical aspects of machine learning, Launch Lecture programme.
  • Eight "Seminar++" meetings centred around presenting open problems and initiating making progress.
  • Mid-semester Lecture the second lecture event of the ML Theory semester programme on April 12th.
Poster ML Semester Programme