Machine Learning

Course description

The course aims at introducing the students to the main principles and algorithms of modern machine learning, along with some applications in such areas as computer vision and pattern recognition. Topics includes neural networks and deep learning, statistical learning theory, support vector machines, spectral clustering, game-theoretic methods etc.

Course objectives

Upon successful completion of this short course, students should

understand the fundamental theory and methodologies of Machine Learning.

Course outline

· Lecture1: (Prof. Marcello Pelillo)

Ø Neural Networks and Deep Learning

· Lecture2: (Prof. Marcello Pelillo)

Ø Statistical Learning Theory

· Lecture3: (Prof. Marcello Pelillo g)

Ø Support Vector Machines

· Lecture4: (Prof. Marcello Pelillo)

Ø Spectral Clustering

· Lecture5: (Prof. Marcello Pelillo)

Ø Game-theoretic Methods

· Lecture6: (Prof. Marcello Pelillo)

Ø Project

Lecturer

Prof. Marcello Pelillo