Within the CHAIR theme semester, two workshops are organized on the theoretical foundations of ML:
- Workshop 1: high-dimensional statistics in ML, held from August 22 to August 24,
- Workshop 2: Theory of Deep Learning, held from August 29 to August 31
It is free to attend the workshops. More information and registration can be found here:
https://sites.google.com/view/2022toml/home
If possible, please register no later than Thu June 16, so we already now get a feeling how many people will attend.
Within this theme semester, several other activities are organized during the Fall of 2022 at Chalmers to bring together prominent researchers in the theory of machine learning (ML), as well as researchers in the Gothenburg area in Sweden, to discuss and formulate various open theoretical questions of practical interest in ML and to share their recent discoveries.
These activities will be under the supervision of Dr. Babak Hassibi (who will also participate in the two workshops). Dr. Hassibi is the Mose and Lillian S. Bohn Professor of Electrical Engineering and Computing and Mathematical Sciences at California Institute of Technology (Caltech), and also the CTO of NPS – a startup in Zero Accidents autonomous driving.
DNN, Machine Learning