Antoine CHATALIC
Antoine CHATALIC
Personnel CNRS Permanent
Statistical machine learning, large-scale kernel methods, sketching, differential privacy
Site Ampère
Bureau : B373
Téléphone : 04 76 82 64 53
Biographie
(à compléter)
Publications / Travaux
14 documents
Articles dans une revue
- Edoardo Caldarelli, Antoine Chatalic, Adrià Colomé, Cesare Molinari, Carlos Ocampo-Martinez, et al.. Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method. Automatica, 2025, 177 (July), pp.112302. ⟨10.1016/j.automatica.2025.112302⟩. ⟨hal-04885608v2⟩
- Antoine Chatalic, Nicolas Schreuder, Ernesto de Vito, Lorenzo Rosasco. Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling. Journal of Machine Learning Research, 2025, 26 (101), pp.1–55. ⟨hal-05394701⟩
- Antoine Chatalic, Vincent Schellekens, Florimond Houssiau, Yves-Alexandre de Montjoye, Laurent Jacques, et al.. Compressive Learning with Privacy Guarantees. Information and Inference, 2022, 11 (1), pp.251-305. ⟨10.1093/imaiai/iaab005⟩. ⟨hal-02496896v2⟩
- Rémi Gribonval, Antoine Chatalic, Nicolas Keriven, Vincent Schellekens, Laurent Jacques, et al.. Sketching Data Sets for Large-Scale Learning: Keeping only what you need. IEEE Signal Processing Magazine, 2021, 38 (5), pp.12-36. ⟨10.1109/MSP.2021.3092574⟩. ⟨hal-03350599⟩
- Evan Byrne, Antoine Chatalic, Rémi Gribonval, Philip Schniter. Sketched Clustering via Hybrid Approximate Message Passing. IEEE Transactions on Signal Processing, 2019, 67 (17), pp.4556-4569. ⟨10.1109/TSP.2019.2924585⟩. ⟨hal-01991231v2⟩
Communications dans un congrès
- Antoine Chatalic. Approximation de Nyström gloutonne par minimisation de la trace. GRETSI 2025 – XXXème Colloque Francophone de Traitement du Signal et des Images, Aug 2025, Strasbourg, France. ⟨hal-05133574⟩
- Antoine Chatalic, Nicolas Schreuder, Alessandro Rudi, Lorenzo Rosasco. Nyström Kernel Mean Embeddings. ICML 2022 – 39th International Conference on Machine Learning, Jul 2022, Baltimore, United States. ⟨hal-04510239⟩
- Antoine Chatalic, Nicolas Keriven, Rémi Gribonval. Projections aléatoires pour l’apprentissage compressif. GRETSI 2019 − XXVIIème Colloque francophone de traitement du signal et des images, Aug 2019, Lille, France. pp.1-4. ⟨hal-02154803⟩
- Vincent Schellekens, Antoine Chatalic, Florimond Houssiau, Yves-Alexandre de Montjoye, Laurent Jacques, et al.. Compressive k-Means with Differential Privacy. SPARS 2019 – Signal Processing with Adaptive Sparse Structured Representations, Jul 2019, Toulouse, France. pp.1-2. ⟨hal-02154820⟩
- Vincent Schellekens, Antoine Chatalic, Florimond Houssiau, Yves-Alexandre de Montjoye, Laurent Jacques, et al.. Differentially Private Compressive k-Means. ICASSP 2019 – IEEE International Conference on Acoustics, Speech, and Signal Processing, May 2019, Brighton, United Kingdom. pp.7933-7937, ⟨10.1109/ICASSP.2019.8682829⟩. ⟨hal-02060208⟩
- Antoine Chatalic, Rémi Gribonval, Nicolas Keriven. Large-Scale High-Dimensional Clustering with Fast Sketching. ICASSP 2018 – IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, Canada. pp.4714-4718, ⟨10.1109/ICASSP.2018.8461328⟩. ⟨hal-01701121⟩
Pré-publications, Documents de travail
- Antoine Chatalic, Marco Letizia, Nicolas Schreuder, Lorenzo Rosasco. A Scalable Nyström-Based Kernel Two-Sample Test with Permutations. 2025. ⟨hal-05349252⟩
- Rémi Gribonval, Antoine Chatalic, Nicolas Keriven, Vincent Schellekens, Laurent Jacques, et al.. Sketching Datasets for Large-Scale Learning (long version). 2021. ⟨hal-02909766v2⟩
Thèses
- Antoine Chatalic. Efficient and privacy-preserving compressive learning. Machine Learning [cs.LG]. Université de Rennes, 2020. English. ⟨NNT : 2020REN1S030⟩. ⟨tel-03023287v2⟩
Documents récupérés de l’archive ouverte HAL 
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