Prof. Luca Iocchi (Home page)

Dipartimento di Ingegneria informatica automatica e gestionale
“Antonio Ruberti”
Università di Roma “La Sapienza”
Via Ariosto 25, Roma 00185, Italy.
Room B115
E-mail: iocchi@dis.uniroma1.it

Office hours: Monday, 10-12
(please send an e-mail for confirmation)

2011/2012 lectures will be given in the second semester (February 27th - May 31st, 2012).

DIS Via Ariosto 25

Monday 12:00 - 13:30 - Room A7
Thursday 8:30 -11:45 - Room A7

NEWS: Next lecture Thursday 24/5 will start at 9.00.

The objectives of this course are to present a wide spectrum of Machine Learning
methods and algorithms, discuss their properties, convergence criteria and applicability.
The course will also present many examples of successful application of Machine Learning
algorithms in different application scenarios.

The main outcome of the course is the capability of the students of solving learning problems,
by a proper formulation of the problem, a proper choice of the algorithm suitable to solve
the problem and the execution of experimental analysis to evaluate the results obtained.

1. Introduction to machine learning
2. Inductive learning
3. Decision trees
4. Evaluation of hypotheses
5. Bayesian learning
6. Classification with linear models
7. Support vector machines
8. Regression with linear models
9. Artificial neural networks
10. Genetic algorithms
11. Instance Based Learning
12. Multiple learners and boosting
13. Bayesian networks
14. Unsupervised learning and clustering
15. Hidden Markov Models
16. Reinforcement learning
17. Robot learning