Workshop: "Understanding Deep Learning: Generalization, Approximation and Optimization"
During the last decade, deep learning has drawn increasing attention both in machine learning and statistics because of its superb empirical performance in various fields of application, including speech and image recognition, natural language processing, social network filtering, bioinformatics, drug design and board games (e.g. Alpha go, Alpha zero). This raises important and fundamental questions on why these methods are so successful, and to what extent they can be applied to a wide range of problems.
The aim of the workshop is to give a balanced representation of the most recent advances on these topics, from theory to applications, and spanning both statistics, optimization and machine learning topics. The workshop targets primarily (but not exclusively) young researchers, in particular PhD students, postdocs and junior early stage researchers. The workshop will take place over 4 days and consists of tutorial courses given by four world experts in the field, each being comprised of roughly of 3 hours of lectures. Furthermore, some of the junior participants will be given the opportunity to present their current work during the workshop by giving a short (30 minutes) oral presentation and possibly poster presentations