A common theme to many activities in ML today is that mathematical models based on sample data are used to train algorithms to work on real data. Applications include self-driven cars, fraud detection, and recommendations on online shops like Amazon. The conference will bring together people working in approximation theory, inverse problems, optimal transport, multi-scale analysis and statistics, for example.
ML is currently undergoing a massive expansion, due to the unprecedented availability of large amounts of data. The data explosion requires new fast and efficient classification methods. Therefore it is sometimes said that an ML revolution is underway, which is transforming our society. The last decade has seen tremendous improvements by ML in application areas ranging from (bio-) medical sciences, computer vision and finance to name a few. Nowadays ML solutions are deployed on mobile phones such that ML impacts all of our lives.
Fundamental questions are open, such as convergence and convergence rates, or the topology and geometry with which data should be studied. It is important for the mathematical community that mathematics claims its share of ML, and provides a solid underpinning of the ML methods that surround us in daily life. This conference will advocate the connection of many mathematical disciplines like numerical analysis, inverse problems, optimisation, statistics, optimal transport, dynamical systems, partial differential equations to ML. By bringing together world-leading mathematicians, statisticians and data scientists to discuss recent developments in the fundamental understanding of ML we aim to shed light into the mysterious pathways of ML.
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