Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling

Rémi Gribonval, Gilles Blanchard, Nicolas Keriven, Yann Traonmilin. Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling. 2020. ⟨ hal-02536818 ⟩

Compressive Statistical Learning with Random Feature Moments

Rémi Gribonval, Gilles Blanchard, Nicolas Keriven, Yann Traonmilin. Compressive Statistical Learning with Random Feature Moments. 2020. ⟨ hal-01544609v3 ⟩

The geometry of off-the-grid compressed sensing

Clarice Poon, Nicolas Keriven, Gabriel Peyré. The geometry of off-the-grid compressed sensing. 2020. ⟨ hal-02484957 ⟩

Sparse and Smooth: improved guarantees for Spectral Clustering in the Dynamic Stochastic Block Model

Nicolas Keriven, Samuel Vaiter. Sparse and Smooth: improved guarantees for Spectral Clustering in the Dynamic Stochastic Block Model. 2020. ⟨ hal-02484970 ⟩

Sketching for Large-Scale Learning of Mixture Models

Nicolas Keriven, Anthony Bourrier, Rémi Gribonval, Patrick Pérez. Sketching for Large-Scale Learning of Mixture Models. Information and Inference, Oxford University Press (OUP), 2018, 7 (3), pp.447-508. ⟨ 10.1093/imaiai/iax015 ⟩. ⟨ hal-01329195v2 ⟩

NEWMA: a new method for scalable model-free online change-point detection

Nicolas Keriven, Damien Garreau, Iacopo Poli. NEWMA: a new method for scalable model-free online change-point detection. 2018. ⟨ hal-02484988 ⟩

Compressive K-means

Nicolas Keriven, Nicolas Tremblay, Yann Traonmilin, Rémi Gribonval. Compressive K-means. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017), Mar 2017, New Orleans, United States. ⟨ hal-01386077v4 ⟩