Workshop in Advancements in High-Dimensional Methods for Machine Learning

This two-day workshop brings together researchers from computer science, statistical physics, and high-dimensional probability to explore fundamental challenges in machine learning. The event will feature both international and local speakers, covering key interdisciplinary topics such as:

1.     Bayesian inference
2.     Signal processing
3.     Machine learning theory
4.     Rigorous mathematical foundations of machine learning

For who

This event is intended for PhD students, postdocs, and faculty members with a background in the relevant fields. Speakers will tailor their presentations to accommodate a diverse audience, ensuring accessibility while maintaining depth and rigor.

Poster session

A dedicated poster session will provide participants with the opportunity to present their work, exchange ideas, and engage in in-depth discussions with experts across different fields. The goal is to foster collaboration, inspire new research directions, and strengthen connections between different communities working on high-dimensional methods.

Program (tentative)

May 26

8.30 Registration and Coffee

8.45 Opening remarks
9.00 Luca Saglietti

9.45 Soon Hoe Lim

10.30 Coffee

11.00 Federica Gerace

11.45 Ayca Ozcelikkala

12.30 Lunch

13.00 Rosalba Pacelli

13.45 Babak Hassibi

15.30 Poster session and Coffee

17.00 Dinner with speakers

May 27

8.30 Coffee

9.00 Maria Chiara Angelini

9.45 Bernhard Mehlig

10.30 Coffee

11.00 Mauro Pastore

11.45 Johan Wästlund

12.30 Lunch

13.00 Speaker TBC

13.45 Speaker TBC

15.30 Discussions

17.00 End

The event is organized with support from the ICT area of advance and from the Lerici foundation.