Samuel Vaiter
Orcid: 0000-0002-4077-708XAffiliations:
- Université Côte d'Azur, Nice, France
According to our database1,
Samuel Vaiter
authored at least 50 papers
between 2012 and 2024.
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Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
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on orcid.org
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Bibliography
2024
Optim. Lett., January, 2024
Trans. Mach. Learn. Res., 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
IEEE Signal Process. Lett., 2023
Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs.
CoRR, 2023
What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
2022
Implicit Differentiation for Fast Hyperparameter Selection in Non-Smooth Convex Learning.
J. Mach. Learn. Res., 2022
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
2021
Automated Data-Driven Selection of the Hyperparameters for Total-Variation-Based Texture Segmentation.
J. Math. Imaging Vis., 2021
J. Math. Imaging Vis., 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
Sparse and Smooth: improved guarantees for Spectral Clustering in the Dynamic Stochastic Block Model.
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
Refitting Solutions Promoted by ℓ _12 Sparse Analysis Regularizations with Block Penalties.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2019
2018
Optimality of 1-norm regularization among weighted 1-norms for sparse recovery: a case study on how to find optimal regularizations.
CoRR, 2018
2017
SIAM J. Imaging Sci., 2017
J. Math. Imaging Vis., 2017
2016
CoRR, 2016
2014
Low Complexity Regularizations of Inverse Problems. (Régularisations de Faible Complexité pour les Problèmes Inverses).
PhD thesis, 2014
Stein Unbiased GrAdient estimator of the Risk (SUGAR) for Multiple Parameter Selection.
SIAM J. Imaging Sci., 2014
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14).
CoRR, 2014
2013
2012
Proceedings of the 19th IEEE International Conference on Image Processing, 2012