Conference at CIMAT, D3

After the colloquium yesterday and our conference diner in a beautiful restaurant, downtown, we are back to work at the “Montréal – Guanajuato Workshop on Probability and Machine Learning“. Third day, with a focus on machine learning. Courtney Paquette (McGill) was our first plenary speaker on ‘High-dimensional Optimization with Applications to Compute-Optimal Neural Scaling Laws’, then Emilien Joly Joly (CIMAT) second plenary speaker on ‘GROS: A Unified Framework for Robust Aggregation in Metric Spaces with Applications to Machine Learning and Statistics’ , Marouane Il Idrissi (UQAM); Wilson Zuniga Galingo (Texas); Juan Jiminez (Ottawa); James Melbourne (CIMAT), our third plenary speaker on ‘Towards optimal privacy mechanisms under estimated sensitivity’; and finally Imanol Nuñez Morales (CIMAT). It is a great, workshop, thanks again to our sponsors (Quantact, SCOR Foundation for Science, CIMAT and the probability lab of Centre de recherches mathématiques (CRM)), thanks to the organizing team (mainly Dante Mata López, without whom nothing would have been possible), the great and enthusiastic speakers we had, and a terrific location…

Agathe at AAAI’25, Philadelphia

Agathe Fernandes Machado is currently in Philadelphia, to present our paper Sequential Conditional Transport on Probabilistic Graphs for Interpretable Counterfactual Fairness, written with Ewen Gallic

In this paper, we link two existing approaches to derive counterfactuals: adaptations based on a causal graph, and optimal transport. We extend “Knothe’s rearrangement” and “triangular transport” to probabilistic graphical models, and use this counterfactual approach, referred to as sequential transport, to discuss fairness at the individual level. After establishing the theoretical foundations of the proposed method, we demonstrate its application through numerical experiments on both synthetic and real datasets.