Thesis: Similarity Ranking for Biometrics: Theory and Practice. Robin Vogel. [Manuscript] [Slides] (2020)

Publications

  • Learning Fair Scoring Functions: Fairness Definitions, Algorithms and Generalization Bounds for Bipartite Ranking.
    R. Vogel, A. Bellet and S. Clémençon.
    [Article] [Code] [Slides] [Poster] [Video] (AISTATS, 2021)
  • A Multiclass Classification Approach to Label Ranking.
    S. Clémençon and R. Vogel.
    [Article] [Code] [Slides] [Video] (AISTATS, 2020)
  • Weighted Empirical Risk Minimization: Transfer Learning based on Importance Sampling.
    R. Vogel, M. Achab, S. Clémençon and C. Tillier.
    [Article] [Code] [Slides] [Video] (ESANN, 2020)
  • Weighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling.
    R. Vogel, M. Achab, S. Clémençon and C. Tillier.
    [Article] [Code] [Slides] [Video] (ICMA, 2020)
  • On Tree-based Methods for Similarity Learning.
    S. Clémençon and R. Vogel.
    [Article] [Code] [Slides] [Poster] (LOD, 2019)
  • Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning.
    R. Vogel, A. Bellet, S. Clémençon, O. Jelassi and G. Papa.
    [Article] [Code] [Slides] [Poster] (ECML PKDD, 2019)
  • A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization.
    R. Vogel, A. Bellet and S. Clémençon.
    [Article] [Code] [Slides] [Poster] [Video] (ICML, 2018)

Reviewing: NeurIPS 2019, ICML 2020, LOD 2020, NeurIPS 2020, ICML 2021.

Talks and posters