About the seminar

This seminar aims to increase the links between the different laboratories in Saclay in the field of Applied Maths, Statistics and Machine Learning. The Seminar is organized every first Tuesday of the month with 2 presentations followed by a small refreshment. The localization of the seminar will change to accommodate the different labs.

Organization

Due to access restriction, you need to register for the seminar. A link is provided in the description and should also be sent with the seminar announcement. It will also help us organize for the food quantities. If you think you will come, please register! (even if you are unsure)

To not miss the next seminar, please subscribe to the announcement mailing list palaisien@inria.fr.
You can also add the calendar from the seminar to your own calendar (see below).

Next seminars

REGISTER 03 Mar 2026, 12h At Inria Saclay - Amphi Sophie Germain
Antonio Ocello - TBA
TBA
TBA
Charlotte Laclau - There is No Universal Fairness: Lessons from Text Classification to Graph Prediction
Despite extensive research on algorithmic fairness, its adoption in real-world systems remains limited. Drawing on case studies in text classification and graph link prediction, I argue that fairness interventions are inherently context-dependent and rarely transfer across application domains. In particular, structural constraints in graphs and the use of pre-trained models in NLP challenge standard fairness assumptions. Beyond these domain-specific limitations, sensitive attributes are often...
Despite extensive research on algorithmic fairness, its adoption in real-world systems remains limited. Drawing on case studies in text classification and graph link prediction, I argue that fairness interventions are inherently context-dependent and rarely transfer across application domains. In particular, structural constraints in graphs and the use of pre-trained models in NLP challenge standard fairness assumptions. Beyond these domain-specific limitations, sensitive attributes are often partially observed or entirely unavailable, and static fairness analyses overlook the long-term feedback effects induced by deployed systems. I'll conclude with reflections on the implications of this context-dependence for both researchers and practitioners.
REGISTER 07 Apr 2026, 12h At Inria Saclay - Amphi Sophie Germain

Scientific Committee

The program and the organization of this seminar is driven by a scientific committee composed of members of the different laboratories in Saclay. The members of the committee are currently:

Funding

This seminar is made possible with financial support of the ENSAE and DataIA.