Large-Scale High-Dimensional Clustering with Fast Sketching. - Antoine Chatalic; Rémi Gribonval; Nicolas Keriven (ICASSP, 2018)

Differentially Private Compressive K-means. - Vincent Schellekens; Antoine Chatalic; Florimond Houssiau; Yves-Alexandre de Montjoye; Laurent Jacques; Rémi Gribonval (ICASSP, 2019)

Sketched Clustering via Hybrid Approximate Message Passing. - Evan Byrne; Antoine Chatalic; Rémi Gribonval; Philip Schniter (IEEE Trans. Signal Process., 2019)

Sketching Datasets for Large-Scale Learning (long version). - Rémi Gribonval; Antoine Chatalic; Nicolas Keriven; Vincent Schellekens; Laurent Jacques; Philip Schniter (CoRR, 2020)

Efficient and Privacy-Preserving Compressive Learning. (Méthodes efficaces pour l'apprentissage compressif avec garanties de confidentialité). - Antoine Chatalic (2020)

Sketching Data Sets for Large-Scale Learning: Keeping only what you need. - Rémi Gribonval; Antoine Chatalic; Nicolas Keriven; Vincent Schellekens; Laurent Jacques; Philip Schniter (IEEE Signal Process. Mag., 2021)

Mean Nyström Embeddings for Adaptive Compressive Learning. - Antoine Chatalic; Luigi Carratino; Ernesto De Vito; Lorenzo Rosasco (AISTATS, 2022)

Nyström Kernel Mean Embeddings. - Antoine Chatalic; Nicolas Schreuder; Lorenzo Rosasco; Alessandro Rudi (ICML, 2022)

M2M: A General Method to Perform Various Data Analysis Tasks from a Differentially Private Sketch. - Florimond Houssiau; Vincent Schellekens; Antoine Chatalic; Shreyas Kumar Annamraju; Yves-Alexandre de Montjoye (STM, 2022)

Heteroscedastic Gaussian Processes and Random Features: Scalable Motion Primitives with Guarantees. - Edoardo Caldarelli; Antoine Chatalic; Adrià Colomé; Lorenzo Rosasco; Carme Torras (CoRL, 2023)

Estimating Koopman operators with sketching to provably learn large scale dynamical systems. - Giacomo Meanti; Antoine Chatalic; Vladimir Kostic; Pietro Novelli; Massimiliano Pontil; Lorenzo Rosasco (NeurIPS, 2023)

Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling. - Antoine Chatalic; Nicolas Schreuder; Ernesto De Vito; Lorenzo Rosasco (CoRR, 2023)

Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method. - Edoardo Caldarelli; Antoine Chatalic; Adrià Colomé; Cesare Molinari; Carlos Ocampo-Martinez; Carme Torras; Lorenzo Rosasco (Autom., 2025)

An Efficient Permutation-Based Kernel Two-Sample Test. - Antoine Chatalic; Marco Letizia; Nicolas Schreuder; Lorenzo Rosasco (CoRR, 2025)