The school will be held in person, at the Milano-Bicocca University in Milan, from Monday 12th September to Friday 16th September.
Monday, Tuesday and Wednesday: U4-08
Thursday and Friday: U3-02
U4-4 (A to C), U4-5 (D to J), U4-6 (K to RA), U4-7 (RE to Z)
All rooms and spaces are located in the same building: Edificio Tellus (Ex U4), Università Milano Bicocca. Piazza della Scienza, 4, 20126 Milano MI.
Detailed information on how to reach the rooms can be found on this document.
The school will cover the following topics:
Foundations, including the basics of deep learning, computer vision, natural language processing, generative models and reinforcement learning;
Advanced topics, featuring large-scale models, graph neural networks, meta-learning and multi-task learning;
Applications of ML to science fields
Ethics and fairness
Upon speakers' approval, the lectures will be recorded and uploaded to our YouTube channel, as well as posted on our website after the school. In addition to direct in-person participation, we will use text-based platforms for questions and discussions (e.g., Slack, Sli.do).
Social Events: Attendees are invited at two social events during the course of the summer school: 1) welcome drinks at Bar Bianco, Sempione Park (Address), Sunday September 11th at 17.45. 2) social dinner at Santeria, Thursday September 15th at 20.00.
Poster sessions: Attendees who wish to present a research poster are encouraged to indicate this in their application to the school. Accepted participants who expressed an interest in presenting a poster will be asked to provide a title and an abstract a few weeks before the school. Contextually, instructions on the poster format will also be provided. Dedicated spaces for posters will be provided at the venue.
Laboratories: Attendees will be split into smaller groups to attend the labs. The labs will consist of coding exercises, with a description of the task, some boilerplate code (data loading, preprocessing, etc, ...) already provided and some blanks to be filled in by the participants. Each group will be supervised by one or more tutors who will explain the exercises and will be there for the duration of the laboratory to answer questions and provide guidance to the participants. The participants will be encouraged to ask questions and interact with the tutors and among themselves to solve the tasks.
Sponsor booths: Diamond sponsors will be at the venue on two days to interact with the attendees, provide information on the applications of ML and AI at their company and discuss job opportunities with interested participants during coffee and lunch breaks. This is a unique opportunity to get to know them better and establish connections, so don't hold back!