PhD-Summer Course- March 17-21, 2014, Genova, Italia



Machine Learning: A Computational Intelligence Approach

MLCI 2014 (1st edition)




 link

Instructors:
Francesco Masulli DIBRIS - UniGe (email: francesco.masulli@unige.it)
Stefano Rovetta
 DIBRIS - UniGe (email: stefano.rovetta@unige.it)

Period: March 17-21, 2014    (Mon-Thu 11:00 am - 1:00 pm and 2:00 pm - 4:00 pm; Fri 11:00 am - 1:00 pm  only)        `

Number of hours: 18 

Summary: The Computational Intelligence is a set of methodologies for information processing inspired by natural systems that in recent decades have been successfully applied to the solution of complex problems. Among them, one can mention the Neural Networks, the Evolutionary Algorithms, the Swarm Intelligence models, the Simulated Annealing, and the Fuzzy sets and Systems. In this course we present some applications of Computational Intelligence methods to supervised and unsupervised problems of Machine Learning.

Syllabus: Supervised Classification, Neural Networks, Evaluation of Classifiers, Introduction to Clustering, Statistical Clustering, Fuzzy Sets, Fuzzy Clustering, Evolutionary Algorithms, Evolutionary Clustering, Applications.

WEB PAGE: UniGE Moodle site

In collaboration with:
dibris
 sig-l
cis
ieee

siren
 shro

Basic Info

Venue:  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 traveling information.

Genova is in the region of Liguria in the Italian Riviera (see here or here for some nice pics and a video).

Accomodations: Here you can find a list of hotels near the department (~ 20' walk) or in the city centre (~20' by bus).

Lunch: Here is a list of places where you can go for lunch. And here is a link to the online Google map.

More Info

Credits and Exams: If you attend most of the classes you will be attributed 6 credits with the DIBRIS metric (or 2 credits according to the ECTS grading scale). The credits attribution will be reported on the certificate of attendance we will handle at the end of the course.

If you need an evaluation, the exam will consist in a sw project or in a seminar.

Prerequisites: Calculus, Linear Algebra, Statistics