Statistics and Learning Theory in the Era of Artificial Intelligence
The workshop highlighted recent theoretical advances on inference in high-dimensional statistical models based on the interplay of techniques from mathematical statistics, machine learning, theoretical computer science and related areas. The workshop brought together about 50 researchers in order to present new results, exchange ideas and explore open problems.
Authors
- Florentina Bunea (ORCID: https://orcid.org/0000-0002-1291-1210)
- Sara van de Geer (ORCID: https://orcid.org/0000-0001-7181-2872)
- Arnak S. Dalalyan (ORCID: https://orcid.org/0000-0003-0054-3227)
- Robert Nowak (ORCID: https://orcid.org/0000-0003-3037-644X)
Institutions
- University of Wisconsin–Madison (US)
- Cornell University (US)
- ETH Zurich (CH)
- ENSAE Paris (FR)
Publication Details
- Journal
- Oberwolfach Reports
- Published
- 2024-11-25
- DOI
- https://doi.org/10.4171/owr/2024/30
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00