Karim Lounici

According to our database, Karim Lounici authored at least 32 papers between 2009 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Geometric Dictionary Learning of Dynamical Systems with Optimal Transport.

Thibaut Germain, Sami Chemlal, Rémi Flamary, Vladimir R. Kostic, Karim Lounici

CoRR, May, 2026

Toeplitz Based Spectral Methods for Data-driven Dynamical Systems.

Vladimir R. Kostic, Karim Lounici, Massimiliano Pontil

CoRR, February, 2026

VertCoHiRF: Decentralized Vertical Clustering Beyond k-means.

Bruno Belucci, Karim Lounici, Vladimir R. Kostic, Katia Meziani

CoRR, February, 2026

AdaCap: An Adaptive Contrastive Approach for Small-Data Neural Networks.

Bruno Belucci, Karim Lounici, Katia Meziani

Proceedings of the 34th European Symposium on Artificial Neural Networks, 2026

2025

kooplearn: A Scikit-Learn Compatible Library of Algorithms for Evolution Operator Learning.

Giacomo Turri, Grégoire Pacreau, Giacomo Meanti, Timothée Devergne, Daniel Ordonez, Erfan Mirzaei, Bruno Belucci, Karim Lounici, Vladimir Kostic, Massimiliano Pontil, Pietro Novelli

CoRR, December, 2025

Toward Scalable and Valid Conditional Independence Testing with Spectral Representations.

Alek Fröhlich, Vladimir Kostic, Karim Lounici, Daniel Perazzo, Massimiliano Pontil

CoRR, December, 2025

Outcome-Aware Spectral Feature Learning for Instrumental Variable Regression.

Dimitri Meunier, Jakub Wornbard, Vladimir R. Kostic, Antoine Moulin, Alek Fröhlich, Karim Lounici, Massimiliano Pontil, Arthur Gretton

CoRR, December, 2025

A Spectral-Grassmann Wasserstein metric for operator representations of dynamical systems.

Thibaut Germain, Rémi Flamary, Vladimir R. Kostic, Karim Lounici

CoRR, September, 2025

Equivariant Representation Learning for Symmetry-Aware Inference with Guarantees.

Daniel Felipe Ordoñez Apraez, Vladimir Kostic, Alek Fröhlich, Vivien Brandt, Karim Lounici, Massimiliano Pontil

CoRR, May, 2025

CoHiRF: A Scalable and Interpretable Clustering Framework for High-Dimensional Data.

Bruno Belucci, Karim Lounici, Katia Meziani

CoRR, February, 2025

Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups.

Vladimir R. Kostic, Karim Lounici, Hélène Halconruy, Timothée Devergne, Pietro Novelli, Massimiliano Pontil

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment.

Théo Gnassounou, Antoine Collas, Rémi Flamary, Karim Lounici, Alexandre Gramfort

CoRR, 2024

Neural Conditional Probability for Inference.

Vladimir R. Kostic, Karim Lounici, Grégoire Pacreau, Pietro Novelli, Giacomo Turri, Massimiliano Pontil

CoRR, 2024

Contextual Continuum Bandits: Static Versus Dynamic Regret.

Arya Akhavan, Karim Lounici, Massimiliano Pontil, Alexandre B. Tsybakov

CoRR, 2024

Neural Conditional Probability for Uncertainty Quantification.

Vladimir Kostic, Grégoire Pacreau, Giacomo Turri, Pietro Novelli, Karim Lounici, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Learning the Infinitesimal Generator of Stochastic Diffusion Processes.

Vladimir Kostic, Hélène Halconruy, Timothée Devergne, Karim Lounici, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Consistent Long-Term Forecasting of Ergodic Dynamical Systems.

Vladimir R. Kostic, Karim Lounici, Prune Inzerilli, Pietro Novelli, Massimiliano Pontil

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning invariant representations of time-homogeneous stochastic dynamical systems.

Vladimir R. Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, Massimiliano Pontil

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Deep projection networks for learning time-homogeneous dynamical systems.

Vladimir R. Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, Massimiliano Pontil

CoRR, 2023

Koopman Operator Learning: Sharp Spectral Rates and Spurious Eigenvalues.

Vladimir Kostic, Karim Lounici, Pietro Novelli, Massimiliano Pontil

CoRR, 2023

Robust covariance estimation with missing values and cell-wise contamination.

Grégoire Pacreau, Karim Lounici

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Sharp Spectral Rates for Koopman Operator Learning.

Vladimir Kostic, Karim Lounici, Pietro Novelli, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-task Representation Learning with Stochastic Linear Bandits.

Leonardo Cella, Karim Lounici, Grégoire Pacreau, Massimiliano Pontil

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Meta Representation Learning with Contextual Linear Bandits.

Leonardo Cella, Karim Lounici, Massimiliano Pontil

CoRR, 2022

AdaCap: Adaptive Capacity control for Feed-Forward Neural Networks.

Katia Meziani, Karim Lounici, Benjamin Riu

CoRR, 2022

Multi-task Representation Learning with Stochastic Linear Bandits.

Leonardo Cella, Karim Lounici, Massimiliano Pontil

CoRR, 2022

2021

Muddling Label Regularization: Deep Learning for Tabular Datasets.

Karim Lounici, Katia Meziani, Benjamin Riu

CoRR, 2021

Muddling Labels for Regularization, a novel approach to generalization.

Karim Lounici, Katia Meziani, Benjamin Riu

CoRR, 2021

2020

Optimizing generalization on the train set: a novel gradient-based framework to train parameters and hyperparameters simultaneously.

Karim Lounici, Katia Meziani, Benjamin Riu

CoRR, 2020

2019

Large scale Lasso with windowed active set for convolutional spike sorting.

Laurent Dragoni, Rémi Flamary, Karim Lounici, Patricia Reynaud-Bouret

CoRR, 2019

Concentration bounds for linear Monge mapping estimation and optimal transport domain adaptation.

Rémi Flamary, Karim Lounici, André Ferrari

CoRR, 2019

2009

Taking Advantage of Sparsity in Multi-Task Learning.

Karim Lounici, Massimiliano Pontil, Alexandre B. Tsybakov, Sara A. van de Geer

Proceedings of the COLT 2009, 2009