Série de conférences mensuelles, le Colloquium Jacques Morgenstern expose les recherches les plus actives et les plus prometteuses dans le domaine des Sciences et Technologies de l’Information et de la Communication (STIC).
Les orateurs, français ou étrangers, sont des personnalités de premier plan, informaticiens, mathématiciens ou spécialistes de domaines où l'informatique est appelée à jouer un rôle majeur.
Les exposés couvrent une problématique suffisamment large pour intéresser tous les chercheurs, ingénieurs et étudiants concernés par l’avenir des STIC.
Le colloquium porte le nom de Jacques Morgenstern, professeur de mathématiques à l'Université de Nice Sophia Antipolis, spécialiste de la théorie de la complexité algébrique et l’un des pionniers du calcul formel. Il a dirigé jusqu’à son décès tragique en 1994 une équipe commune à l’Université de Nice Sophia Antipolis, Inria et le CNRS.
Le colloquium est un élément de la formation de l’Ecole Doctorale STIC. Entrée libre.
Les orateurs, français ou étrangers, sont des personnalités de premier plan, informaticiens, mathématiciens ou spécialistes de domaines où l'informatique est appelée à jouer un rôle majeur.
Les exposés couvrent une problématique suffisamment large pour intéresser tous les chercheurs, ingénieurs et étudiants concernés par l’avenir des STIC.

Le colloquium est un élément de la formation de l’Ecole Doctorale STIC. Entrée libre.
Nos derniers orateurs

Fabio Cozman – Research in Knowledge-Enhanced Machine Learning at the Center for Artificial Intelligence (C4AI)
January 5th, 2023 This talk will first describe activities and research projects in the Center for Artificial Intelligence (C4AI) headquartered at the University of São Paulo, from language processing to physics-based machine learning. The second part of the talk will focus on a number of connections between machine learning and knowledge representation, dealing with explainability,…

Catuscia Palamidessi – Information Structures for Privacy and Fairness
December 15th, 2022 The increasingly pervasive use of big data and machine learning is raising various ethical issues, in particular privacy and fairness. In this talk, I will discuss some frameworks to understand and mitigate the issues, focusing on iterative methods coming from information theory and statistics. In the area of privacy protection, differential privacy (DP) and…

Claude Castelluccia – AI and Human Decision-Making: An Interdisciplinary Perspective
November 22nd, 2022 – 11:00 am Algorithm Decision Systems are currently being designed to help humans in decision-making. For example, they are used to identify suspicious behaviours, detect hate speech or predict crimes. The impact of these systems on people and the society can be significant. This seminar will talk about some of the privacy risks of…

John Shawe-Taylor – Statistical Learning Theory for Modern Machine Learning
September 30th, 2022 – 10:30 am The talk introduces the motivation behind statistical learning theory and after reviewing some earlier approaches gives an overview of the PAC-Bayes methodology to analysing generalisation, highlighting the links between Bayesian and frequentist ideas that it embodies. Its application to Support Vector Machines and Deep Neural Networks will be discussed…

Ioana Manolescu – Teasing journalistic findings out of heterogeneous sources: a data/AI journey
June 2nd, 2022 Freedom of the press is under threat worldwide, and the quality of information that people have access to is dangerously degraded, under the joint threat of non-democratic governments and fake information propagation. The press as an industry needs powerful data management tools to help them interpret the complex reality surrounding us. Since…

Sabine Süsstrunk – Opponency revisited
March 10th, 2022 – 11:00 am According to the efficient coding hypothesis, the goal of the visual system should be to encode the information presented to the retina with as little redundancy as possible. From a signal processing point of view, the first step in removing redundancy is de-correlation, which removes the second order dependencies…