Laurent Risser

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

◀ ▶ joint publications with Fanny Jourdan

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Publications

2023
[j18]
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Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes, Laurent Risser:
How Optimal Transport Can Tackle Gender Biases in Multi-Class Neural Network Classifiers for Job Recommendations. Algorithms 16(3): 174 (2023)
[c27]
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Fanny Jourdan, Agustin Martin Picard, Thomas Fel, Laurent Risser, Jean-Michel Loubes, Nicholas Asher:
COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP. ACL (Findings) 2023: 5120-5136
[c26]
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Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes, Laurent Risser:
Breaking Bias: How Optimal Transport Can Help to Tackle Gender Biases in NLP Based Job Recommendation Systems? EWAF 2023
[c25]
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Fanny Jourdan, Ronan Pons, Nicholas Asher, Jean-Michel Loubes, Laurent Risser:
Is a Fairness Metric Score Enough to Assess Discrimination Biases in Machine Learning? EWAF 2023
[i14]
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  - journals/corr/abs-2302-14063
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Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes, Laurent Risser:
How optimal transport can tackle gender biases in multi-class neural-network classifiers for job recommendations? CoRR abs/2302.14063 (2023)
[i13]
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  - journals/corr/abs-2305-06754
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Fanny Jourdan, Agustin Martin Picard, Thomas Fel, Laurent Risser, Jean-Michel Loubes, Nicholas Asher:
COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP tasks. CoRR abs/2305.06754 (2023)
[i12]
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  - journals/corr/abs-2306-05307
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Fanny Jourdan, Laurent Risser, Jean-Michel Loubes, Nicholas Asher:
Are fairness metric scores enough to assess discrimination biases in machine learning? CoRR abs/2306.05307 (2023)
[i10]
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  - journals/corr/abs-2312-06499
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Fanny Jourdan, Louis Béthune, Agustin Picard, Laurent Risser, Nicholas Asher:
TaCo: Targeted Concept Removal in Output Embeddings for NLP via Information Theory and Explainability. CoRR abs/2312.06499 (2023)

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