Antoine Chatalic

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 16

Top Topics

Gaussian Process

Differentially Private

Top Venues

IEEE Trans. Signal Process.

Publications

Edoardo Caldarelli, Antoine Chatalic, Adrià Colomé, Cesare Molinari, Carlos Ocampo-Martinez, Carme Torras, Lorenzo Rosasco
Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method. CoRR (2024)
Giacomo Meanti, Antoine Chatalic, Vladimir R. Kostic, Pietro Novelli, Massimiliano Pontil, Lorenzo Rosasco
Estimating Koopman operators with sketching to provably learn large scale dynamical systems. CoRR (2023)
Giacomo Meanti, Antoine Chatalic, Vladimir Kostic, Pietro Novelli, Massimiliano Pontil, Lorenzo Rosasco
Estimating Koopman operators with sketching to provably learn large scale dynamical systems. NeurIPS (2023)
Antoine Chatalic, Nicolas Schreuder, Ernesto De Vito, Lorenzo Rosasco
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling. CoRR (2023)
Edoardo Caldarelli, Antoine Chatalic, Adrià Colomé, Lorenzo Rosasco, Carme Torras
Heteroscedastic Gaussian Processes and Random Features: Scalable Motion Primitives with Guarantees. CoRL (2023)
Florimond Houssiau, Vincent Schellekens, Antoine Chatalic, Shreyas Kumar Annamraju, Yves-Alexandre de Montjoye
M: A General Method to Perform Various Data Analysis Tasks from a Differentially Private Sketch. STM (2022)
Antoine Chatalic, Nicolas Schreuder, Lorenzo Rosasco, Alessandro Rudi
Nyström Kernel Mean Embeddings. ICML (2022)
Antoine Chatalic, Nicolas Schreuder, Alessandro Rudi, Lorenzo Rosasco
Nyström Kernel Mean Embeddings. CoRR (2022)
Florimond Houssiau, Vincent Schellekens, Antoine Chatalic, Shreyas Kumar Annamraju, Yves-Alexandre de Montjoye
M: A general method to perform various data analysis tasks from a differentially private sketch. CoRR (2022)
Antoine Chatalic, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco
Mean Nyström Embeddings for Adaptive Compressive Learning. AISTATS (2022)
Antoine Chatalic, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco
Mean Nyström Embeddings for Adaptive Compressive Learning. CoRR (2021)
Rémi Gribonval, Antoine Chatalic, Nicolas Keriven, Vincent Schellekens, Laurent Jacques, Philip Schniter
Sketching Data Sets for Large-Scale Learning: Keeping only what you need. IEEE Signal Process. Mag. 38 (5) (2021)
Rémi Gribonval, Antoine Chatalic, Nicolas Keriven, Vincent Schellekens, Laurent Jacques, Philip Schniter
Sketching Datasets for Large-Scale Learning (long version). CoRR (2020)
Evan Byrne, Antoine Chatalic, Rémi Gribonval, Philip Schniter
Sketched Clustering via Hybrid Approximate Message Passing. IEEE Trans. Signal Process. 67 (17) (2019)
Vincent Schellekens, Antoine Chatalic, Florimond Houssiau, Yves-Alexandre de Montjoye, Laurent Jacques, Rémi Gribonval
Differentially Private Compressive K-means. ICASSP (2019)
Antoine Chatalic, Rémi Gribonval, Nicolas Keriven
Large-Scale High-Dimensional Clustering with Fast Sketching. ICASSP (2018)