Nathan Noiry
According to our database1,
Nathan Noiry
authored at least 15 papers
between 2021 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
Learning to rank anomalies: scalar performance criteria and maximization of rank statistics.
Mach. Learn., December, 2024
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
2023
A Functional Data Perspective and Baseline On Multi-Layer Out-of-Distribution Detection.
CoRR, 2023
Proceedings of the Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023, 2023
A Novel Information Theoretic Objective to Disentangle Representations for Fair Classification.
Proceedings of the Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023, 2023
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
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
Proceedings of the International Conference on Machine Learning, 2022
Learning Disentangled Textual Representations via Statistical Measures of Similarity.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
2021
Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Learning to Rank Anomalies: Scalar Performance Criteria and Maximization of Two-Sample Rank Statistics.
Proceedings of the Third International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021