Analysis of multidimensional data 2017-18

PhD in Computer Science

Academic year

The course aims at illustrating some advanced topics from the multivariate analysis realm.

Course schedule

Lectures will take place at the Computer science department in the meeting room at 1st floor.

Office hours

By appointment. It is possible contact the teacher by e-mail, taking care to read in advance the guide prepared by Prof. Sebastiano Vigna and clearly specifying in the message the course name and the academic year. In particular, students are encouraged to always use their academic address (i.e. based on the domain signing with name and student ID number and recalling that the response time may vary depending on the teacher commitments.

Course material

The course is based on the following textbook: A. J. Izenman, Modern Multivariate Statistical Techniques, Springer (ISBN: 987-0-387-78188-4).

Preliminary reading of some notes on the matrix differential calculus is recommended.


Multivariate distributions: properties of the normal distribution, parametric inference, nonparametric inference. Linear discriminand analysis, logistic regressione. Multivariate linear regression. Nonlinear regression through SVM.

Students are invited to fill in an evaluation form.

Exam modalities

The exam consists in the discussion of a project to be agreed with teachers.