Talks

  • Addressing Interpretability, Fairness & Privacy in Machine Learning Through Combinatorial Optimization Methods - PhD Defense (LAAS-CNRS, Toulouse, France) - recording
  • Exploiting Fairness to Enhance Sensitive Attributes Reconstruction - PrivSec team Seminar 2023 (UQAM/ETS, Montréal, Canada (online))
  • Exploiting Fairness to Enhance Sensitive Attributes Reconstruction - RJCIA 2023 (Strasbourg, France)
  • Exploiting Fairness to Enhance Sensitive Attributes Reconstruction - ROADEF 2023 (Rennes, France)
  • Exploiting Fairness to Enhance Sensitive Attributes Reconstruction - SATML 2023 (Raleigh, North Carolina, USA) - recording
  • Operational Research for Fairness, Privacy and Interpretability in Machine Learning: Leveraging ILP to Learn Optimal Fair Rule Lists - DS4DM Coffee Talks (Polytechnique Montréal) - recording
  • Leveraging Integer Linear Programming to Learn Optimal Fair Rule Lists - CPAIOR 2022 (Los Angeles, California, USA) - recording
  • Operational Research for Fairness, Privacy and Interpretability in Machine Learning: Leveraging ILP to Learn Optimal Fair Rule Lists - Golnoosh Farnadi research group seminar (MILA, Montréal, Canada)
  • Operational Research for Fairness, Privacy and Interpretability in Machine Learning: Leveraging ILP to Learn Optimal Fair Rule Lists - LATECE seminar (UQAM, Montréal, Canada)
  • Leveraging Integer Linear Programming to Learn Optimal Fair Rule Lists - PrivSec team Seminar 2022 (UQAM, Montréal, Canada)
  • Leveraging MILP to Conciliate Statistical Fairness and Accuracy in Interpretable ML: Learning Optimal Fair Rule Lists - ROADEF 2022 (Lyon, France)
  • FairCORELS, an Open-Source Library for Learning Fair Rule Lists - CIKM 2021 (Gold Coast, Queensland, Australia (online)) - recording
  • Distributionally Robust Optimization to Improve Fairness Generalization in Machine Learning - LAAS-CNRS Decision & Optimization Department Workshop (Mauvezin, France)
  • Addressing Interpretability, Fairness and Privacy in ML Through Combinatorial Optimization Methods - GDR IA Autumn School (IA²) - Poster Session (Paris, France)
  • Distributionally Robust Optimization to Improve Fairness Generalization in Machine Learning - RJCIA 2021 (Bordeaux, France (online))
  • Distributionally Robust Optimization to Improve Fairness Generalization in Machine Learning - ROADEF 2021 (Mulhouse, France (online)
  • Bias in Machine Learning - LAAS-CNRS ROC Team seminar (Toulouse, France)