Corsi Anno Accademico 2024/2025

Optimization algorithms for AI and learning algorithms for optimization problems

Course objectives

This course aims at elucidating the deep links between mathematical optimisation and machine learning. The students will be introduced to the following themes and abilities: understand the properties of different kinds of non-linear continuous optimisation algorithms to tune the (hyper-)parameters of machine learning models and how to apply them; understand how to model some advanced machine learning models as bi-level optimisation models; identify situations where machine learning and process mining can be used as a sub-module for combinatorial optimisation problems.

Course delivery

The lectures consist of 24 hours divided between the three themes previously described (respectively 10h/10h/4h) and will take place on Wednesdays afternoons between 1pm and 5pm on the following dates: 2/4/2025, 9/4/2025, 16/4/2025, 30/4/2025, 7/5/2025 and 14/5/2025 at the Computer Science Department of the University of Turin. For students who cannot attend physically, the lectures will be available in streaming

Further details: https://dott-informatica.campusnet.unito.it/do/corsi.pl/Show?_id=z84t

Emotion Oriented Systems 2025

- Introduction to the course: overview on emotion oriented systems
- Emotions: concepts, definitions and models: from psychological theories to
computational models 
- Linguistic and semantic resources: datasets, sentiment lexicons (multilingualism),
ontologies; collecting and labelling methodologies; available benchmarks and
standards.
- Application I: Emotions in interaction: emotions in virtual agents; practical
architectures for emotion generation and expression
- Application II: Emotion detection and sentiment analysis in social media:
state-of-the-art methodologies, application domains

Cloud Computing for Science 2025

See https://dott-informatica.campusnet.unito.it/do/corsi.pl/Show?_id=gu2e

Introduction to Deep Learning 2025