Fundamentals of Representation Learning

At the 9th International Summer School on AI and Big Data, Dr. Sahar Vahdati (InfAI) will talk about Fundamentals of Representation Learning. The keynote will take place on Friday 07.07.2023 from 09 a.m. – 10:30 a.m.

Keynote: Fundamentals of Representation Learning

Deep learning approaches have been used very successfully to automatically find appropriate representations of input data in order to solve machine learning tasks. One particularly relevant, but also challenging, type of input data are knowledge graphs (KGs) that encode human knowledge. Currently, most deep learning approaches for representation learning in knowledge graphs are empirically driven. There is a lack of a clear mathematical understanding of how deep learning approaches can capture the complexity of human knowledge in specific application domains. In this talk, you will be introduced to basics concepts of representation learning, linear algebra and knowledge graphs and embedding models.

Dr. Sahar Vahdati

Dr. Sahar Vahdati is a research group lead at the Institute of Applied Computer Science (InfAI) at the University of Leipzig. Her group, Nature-Inspired Machine Intelligence (NIMI) focuses on research in machine intelligence inspired by natural science such as Nature in Knowledge Representation and Reasoning, Natural Sciences in Knowledge Discovery and Data Mining with Embeddings/Neural Networks, Applications of Machine Intelligence for Social good. Prior to this, she was a postdoctoral fellow in the computer science department of Oxford University.

Read more about the 9th International Summer School on AI and Big Data.