• Accelerating Spectral Clustering under Fairness Constraints (ICML 2025)
    Francesco Tonin, Alex Lambert, Johan Suykens, Volkan Cevher (paper)

  • Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method (ICML 2024)
    Qinghua Tao, Francesco Tonin, Alex Lambert, Yingyi Chen, Panos Patrinos, Johan Suykens (paper)

  • Extending Kernel PCA through Dualization: Sparsity, Robustness, and Fast Algorithms (ICML 2023)
    Francesco Tonin*, Alex Lambert*, Panos Patrinos, Johan Suykens (paper, code)

  • Functional Output Regression with Infimal Convolution: Exploring the Huber and ε-insensitive Losses (ICML 2022)
    Alex Lambert, Dimitri Bouche, Zoltan Szabo, Florence d’Alché-Buc (paper, code)

  • Emotion Transfer Using Vector-Valued Infinite Task Learning (preprint)
    Alex Lambert*, Sanjeel Parekh*, Zoltan Szabo, Florence d’Alché-Buc (paper, code)

  • Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses (ICML 2020)
    Pierre Laforgue, Alex Lambert, Luc Brogat-Motte, Florence d’Alché-Buc (paper)

  • A Functional Extension of Multi-Output Learning (AMTL Workshop, ICML 2019)
    Alex Lambert*, Romain Brault*, Zoltan Szabo, Florence d’Alché-Buc (paper)

  • Infinite Task Learning in RKHSs (AISTATS 2019)
    Romain Brault*, Alex Lambert*, Zoltan Szabo, Maxime Sangnier, Florence d’Alché-Buc (paper, poster, code)