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Nathan Noiry
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2020 – today
- 2024
- [c11]Anas Himmi, Ekhine Irurozki, Nathan Noiry, Stéphan Clémençon, Pierre Colombo:
Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks. EMNLP (Findings) 2024: 11759-11785 - 2023
- [c10]Pierre Colombo, Marine Picot, Nathan Noiry, Guillaume Staerman, Pablo Piantanida:
Toward Stronger Textual Attack Detectors. EMNLP (Findings) 2023: 484-505 - [c9]Pierre Colombo, Maxime Peyrard, Nathan Noiry, Robert West, Pablo Piantanida:
The Glass Ceiling of Automatic Evaluation in Natural Language Generation. IJCNLP (Findings) 2023: 178-183 - [c8]Pierre Colombo, Nathan Noiry, Guillaume Staerman, Pablo Piantanida:
A Novel Information Theoretic Objective to Disentangle Representations for Fair Classification. IJCNLP (Findings) 2023: 184-198 - [i11]Anas Himmi, Ekhine Irurozki, Nathan Noiry, Stéphan Clémençon, Pierre Colombo:
Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks. CoRR abs/2305.10284 (2023) - [i10]Eduardo Dadalto Câmara Gomes, Pierre Colombo, Guillaume Staerman, Nathan Noiry, Pablo Piantanida:
A Functional Data Perspective and Baseline On Multi-Layer Out-of-Distribution Detection. CoRR abs/2306.03522 (2023) - [i9]Flore Sentenac, Nathan Noiry, Matthieu Lerasle, Laurent Ménard, Vianney Perchet:
Online Matching in Geometric Random Graphs. CoRR abs/2306.07891 (2023) - [i8]Pierre Colombo, Nathan Noiry, Guillaume Staerman, Pablo Piantanida:
A Novel Information-Theoretic Objective to Disentangle Representations for Fair Classification. CoRR abs/2310.13990 (2023) - [i7]Pierre Colombo, Marine Picot, Nathan Noiry, Guillaume Staerman, Pablo Piantanida:
Toward Stronger Textual Attack Detectors. CoRR abs/2310.14001 (2023) - 2022
- [c7]Pierre Colombo, Guillaume Staerman, Nathan Noiry, Pablo Piantanida:
Learning Disentangled Textual Representations via Statistical Measures of Similarity. ACL (1) 2022: 2614-2630 - [c6]Jean-Rémy Conti, Nathan Noiry, Stéphan Clémençon, Vincent Despiegel, Stéphane Gentric:
Mitigating Gender Bias in Face Recognition using the von Mises-Fisher Mixture Model. ICML 2022: 4344-4369 - [c5]Pierre Colombo, Eduardo Dadalto Câmara Gomes, Guillaume Staerman, Nathan Noiry, Pablo Piantanida:
Beyond Mahalanobis Distance for Textual OOD Detection. NeurIPS 2022 - [c4]Pierre Colombo, Nathan Noiry, Ekhine Irurozki, Stéphan Clémençon:
What are the best Systems? New Perspectives on NLP Benchmarking. NeurIPS 2022 - [i6]Pierre Colombo, Nathan Noiry, Ekhine Irurozki, Stéphan Clémençon:
What are the best systems? New perspectives on NLP Benchmarking. CoRR abs/2202.03799 (2022) - [i5]Pierre Colombo, Guillaume Staerman, Nathan Noiry, Pablo Piantanida:
Learning Disentangled Textual Representations via Statistical Measures of Similarity. CoRR abs/2205.03589 (2022) - [i4]Pierre Colombo, Maxime Peyrard, Nathan Noiry, Robert West, Pablo Piantanida:
The Glass Ceiling of Automatic Evaluation in Natural Language Generation. CoRR abs/2208.14585 (2022) - [i3]Jean-Rémy Conti, Nathan Noiry, Vincent Despiegel, Stéphane Gentric, Stéphan Clémençon:
Mitigating Gender Bias in Face Recognition Using the von Mises-Fisher Mixture Model. CoRR abs/2210.13664 (2022) - [i2]Pierre Colombo, Eduardo Dadalto Câmara Gomes, Guillaume Staerman, Nathan Noiry, Pablo Piantanida:
Beyond Mahalanobis-Based Scores for Textual OOD Detection. CoRR abs/2211.13527 (2022) - 2021
- [c3]Patrice Bertail, Stéphan Clémençon, Yannick Guyonvarch, Nathan Noiry:
Learning from Biased Data: A Semi-Parametric Approach. ICML 2021: 803-812 - [c2]Myrto Limnios
, Nathan Noiry, Stéphan Clémençon:
Learning to Rank Anomalies: Scalar Performance Criteria and Maximization of Two-Sample Rank Statistics. LIDTA@ECML/PKDD 2021: 63-75 - [c1]Nathan Noiry, Vianney Perchet, Flore Sentenac:
Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm. NeurIPS 2021: 21400-21412 - [i1]Nathan Noiry, Flore Sentenac, Vianney Perchet:
Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm. CoRR abs/2107.00995 (2021)
Coauthor Index
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