# This School has been cancelled

### MIS-IMH research school on Mathematics of Data

Hanoi, 4-13 March, 2020

**AIM AND OBJECTIVE**

Science is relying increasingly on large data sets. They provide important resources, and we have ever more powerful computational devices to treat them, but we often lack good prior theories to make sense of them or hypotheses to test on them. We therefore need novel formal methods to identify and extract meaningful structures in large and intransparent data sets. This is a challenge and an opportunity for mathematics. In fact, ideas from very different mathematical disciplines have been used to provide new tools for data analysis. Topological data analysis uses methods from algebraic topology, manifold learning is inspired by Riemannian geometry, compressed sensing uses Banach space theory, hierarchical decompositions utilize tensor algebra, network analysis has inspired graph theory and currently moves towards hypergraphs, to name but a few examples. In particular, statistics faces new problems, either of large data sets without good model classes or conversely models with many more free parameters than available observations.

This is an exciting situation for mathematics. We want to introduce the participants of this school to those problems and to a wide range of new mathematical techniques, and to prepare them to pursue novel mathematical research.

At this school, we want to provide a stimulating intellectual environment for researchers from Vietnam and neighboring countries in Asia to learn about recent developments in mathematical data science, acquire background knowledge from the relevant mathematical disciplines and interact with leading researchers on concrete topics of mathematical data analysis and statistics. **CONCRETE TOPICS WILL INCLUDE**

- Deep learning theory
- Statistical/probabilistic/optimization foundation for data
- Graph theory and neural networks
- Information complexity

**SCHOOL LOCATION**

Institute of Mathematics, Hanoi (IMH), Vietnam Academy of Science and Technology (VAST).

Address: 18 Hoang Quoc Viet Road, Cau Giay disctrict, 10307 Ha Noi, Vietnam.

**Contact**

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