Antoine Chatalic

1. Estimating Koopman operators with sketching to provably learn large scale dynamical systems
   2023/06/07 by Giacomo Meanti, Antoine Chatalic, Meanti, Giacomo +9 · 3 citations
   Computer Science · Physics and Astronomy · #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Model Reduction and Neural Networks #Neural Networks and Applications
2. Sketching Datasets for Large-Scale Learning (long version)
   2020/08/04 by Rémi Gribonval, Gribonval, Rémi, Antoine Chatalic +9 · 1 citation
   Computer Science · #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Privacy-Preserving Technologies in Data #Stochastic Gradient Optimization Techniques #Topological and Geometric Data Analysis
3. Mean Nyström Embeddings for Adaptive Compressive Learning
   2021/10/21 by Antoine Chatalic, Luigi Carratino, Chatalic, Antoine +5 · 1 citation
   Computer Science · Engineering · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques
4. A Scalable Nystrom-Based Kernel Two-Sample Test with Permutations
   2025/02/19 by Antoine Chatalic, Chatalic, Antoine, Marco Letizia +5 · 2 citations
   Computer Science · Engineering · Mathematics · #Face and Expression Recognition #Sparse and Compressive Sensing Techniques #Advanced Statistical Methods and Models