Instructors
Lorenzo Rosasco
University of Genova
(also Istituto Italiano di Tecnologia and Massachusetts Institute of Technology)
lorenzo [dot] rosasco [at] unige [dot] it
Machine Learning is a key to develop intelligent systems and analyze data in science and engineering. Machine Learning engines enable intelligent technologies such as Siri, Kinect or Google self driving car, to name a few. At the same time, Machine Learning methods help deciphering the information in our DNA and make sense of the flood of information gathered on the web, forming the basis of a new “Science of Data”. This course provides an introduction to the fundamental methods at the core of modern Machine Learning. It covers theoretical foundations as well as essential algorithms. Classes on theoretical and algorithmic aspects are complemented by practical lab sessions.
This introductory course is suitable for undergraduate/graduate students, as well as professionals.
Course Structure:
The course started in 2013 has seen an increasing national and international attendance over the years with a peak of over 100 participants in 2015.
Important dates:
Registration fee (note):
Related courses:
Classes will take place at the Department of Informatics Bioengineering Robotics and Systems Engineering (DIBRIS) of the University of Genova in Via Dodecaneso 35, 16146 Genova. See here for directions and travelling information
Genova is in the region of Liguria in the Italian Riviera (see here or here for some nice pics and a video).
Here you can find a list of hotels near the department (~ 20' walk) or in the city centre (~20' by bus).
Here is a list of places where you can go for lunch. And here is a link to the online map.
For more info write to:
vigogna [at] dibris [dot] unige [dot] it
cristian [dot] rusu [at] iit [dot] it
raffaello [dot] camoriano [at] iit [dot] it
University of Genova
(also Istituto Italiano di Tecnologia and Massachusetts Institute of Technology)
lorenzo [dot] rosasco [at] unige [dot] it
| CLASS | DAY | TIME | SUBJECT | FILES |
| 1 | 06/17 | 9:30 - 11:00 | Introduction to Machine Learning | |
| 2 | 06/17 | 11:30 - 13:00 | Local Methods and Model Selection | |
| 3 | 06/17 | 14:00 - 16:00 | Laboratory 1: Local Methods for Classification | |
| 4 | 06/18 | 9:30 - 11:00 | Regularization Networks I: Linear Models | |
| 5 | 06/18 | 11:30 - 13:00 | Regularization Networks II: Kernels | |
| 6 | 06/18 | 14:00 - 16:00 | Laboratory 2: Regularization Networks | |
| Talk | 06/19 | 9:30 - 10:10 | TBA | |
| Talk | 06/19 | 10:10 - 10:35 | TBA | |
| 06/19 | 11:00 - 11:30 | Coffee Break | ||
| Talk | 06/19 | 11:30 - 12:10 | TBA | |
| Talk | 06/19 | 12:10 - 12:35 | TBA | |
| 06/19 | Afternoon | Free | ||
| 7 | 06/20 | 9:30 - 11:00 | Dimensionality Reduction and PCA | |
| 8 | 06/20 | 11:30 - 13:00 | Variable Selection and Sparsity | |
| 9 | 06/20 | 14:00 - 16:00 | Laboratory 3: PCA and Sparsity | |
| 10 | 06/21 | 9:30 - 11:00 | Clustering | |
| 11 | 06/21 | 11:30 - 13:00 | Data Representation: Deep Learning |
University of Genova (UNIGE)
Laboratory for Computational and Statistical Learning (LCSL)
vigogna [at] dibris [dot] unige [dot] it
Istituto Italiano di Tecnologia (IIT)
Laboratory for Computational and Statistical Learning (LCSL)
cristian [dot] rusu [at] iit [dot] it
Istituto Italiano di Tecnologia (IIT)
Laboratory for Computational and Statistical Learning (LCSL)
raffaello [dot] camoriano [at] iit [dot] it
