Karim Lounici

According to our database1, Karim Lounici authored at least 21 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups.
CoRR, 2024

Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment.
CoRR, 2024

Neural Conditional Probability for Inference.
CoRR, 2024

Contextual Continuum Bandits: Static Versus Dynamic Regret.
CoRR, 2024

Learning the Infinitesimal Generator of Stochastic Diffusion Processes.
CoRR, 2024

Consistent Long-Term Forecasting of Ergodic Dynamical Systems.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning invariant representations of time-homogeneous stochastic dynamical systems.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Deep projection networks for learning time-homogeneous dynamical systems.
CoRR, 2023

Koopman Operator Learning: Sharp Spectral Rates and Spurious Eigenvalues.
CoRR, 2023

Robust covariance estimation with missing values and cell-wise contamination.
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.
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.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Meta Representation Learning with Contextual Linear Bandits.
CoRR, 2022

AdaCap: Adaptive Capacity control for Feed-Forward Neural Networks.
CoRR, 2022

Multi-task Representation Learning with Stochastic Linear Bandits.
CoRR, 2022

2021
Muddling Label Regularization: Deep Learning for Tabular Datasets.
CoRR, 2021

Muddling Labels for Regularization, a novel approach to generalization.
CoRR, 2021

2020
Optimizing generalization on the train set: a novel gradient-based framework to train parameters and hyperparameters simultaneously.
CoRR, 2020

2019
Large scale Lasso with windowed active set for convolutional spike sorting.
CoRR, 2019

Concentration bounds for linear Monge mapping estimation and optimal transport domain adaptation.
CoRR, 2019

2009
Taking Advantage of Sparsity in Multi-Task Learning.
Proceedings of the COLT 2009, 2009


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