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Gabriel Laberge
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Journal Articles
- 2024
- [j4]Moses Openja, Gabriel Laberge, Foutse Khomh:
Detection and evaluation of bias-inducing features in machine learning. Empir. Softw. Eng. 29(1): 22 (2024) - [j3]Khouloud Oueslati, Gabriel Laberge, Maxime Lamothe, Foutse Khomh:
Mining Action Rules for Defect Reduction Planning. Proc. ACM Softw. Eng. 1(FSE): 2309-2331 (2024) - 2023
- [j2]Gabriel Laberge, Yann Pequignot, Alexandre Mathieu, Foutse Khomh, Mario Marchand:
Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon Set. J. Mach. Learn. Res. 24: 364:1-364:50 (2023) - 2022
- [j1]Florian Tambon, Gabriel Laberge, Le An, Amin Nikanjam, Paulina Stevia Nouwou Mindom, Yann Pequignot, Foutse Khomh, Giulio Antoniol, Ettore Merlo, François Laviolette:
How to certify machine learning based safety-critical systems? A systematic literature review. Autom. Softw. Eng. 29(2): 38 (2022)
Conference and Workshop Papers
- 2024
- [c4]Gabriel Laberge, Yann Batiste Pequignot, Mario Marchand, Foutse Khomh:
Tackling the XAI Disagreement Problem with Regional Explanations. AISTATS 2024: 2017-2025 - 2023
- [c3]Gabriel Laberge, Ulrich Aïvodji, Satoshi Hara, Mario Marchand, Foutse Khomh:
Fooling SHAP with Stealthily Biased Sampling. ICLR 2023 - 2022
- [c2]Saumendu Roy, Gabriel Laberge, Banani Roy, Foutse Khomh, Amin Nikanjam, Saikat Mondal:
Why Don't XAI Techniques Agree? Characterizing the Disagreements Between Post-hoc Explanations of Defect Predictions. ICSME 2022: 444-448 - 2019
- [c1]Gabriel Laberge, Shahrzad Shirzad, Patrick Diehl, Hartmut Kaiser, Serge Prudhomme, Adrian S. Lemoine:
Scheduling Optimization of Parallel Linear Algebra Algorithms Using Supervised Learning. MLHPC@SC 2019: 31-43
Informal and Other Publications
- 2024
- [i8]Khouloud Oueslati, Gabriel Laberge, Maxime Lamothe, Foutse Khomh:
Mining Action Rules for Defect Reduction Planning. CoRR abs/2405.13740 (2024) - 2023
- [i7]Julien Ferry, Gabriel Laberge, Ulrich Aïvodji:
Learning Hybrid Interpretable Models: Theory, Taxonomy, and Methods. CoRR abs/2303.04437 (2023) - [i6]Moses Openja, Gabriel Laberge, Foutse Khomh:
Detection and Evaluation of bias-inducing Features in Machine learning. CoRR abs/2310.12805 (2023) - 2022
- [i5]Gabriel Laberge, Ulrich Aïvodji, Satoshi Hara:
Fooling SHAP with Stealthily Biased Sampling. CoRR abs/2205.15419 (2022) - [i4]Gabriel Laberge, Yann Pequignot:
Understanding Interventional TreeSHAP : How and Why it Works. CoRR abs/2209.15123 (2022) - 2021
- [i3]Florian Tambon, Gabriel Laberge, Le An, Amin Nikanjam, Paulina Stevia Nouwou Mindom, Yann Pequignot, Foutse Khomh, Giulio Antoniol, Ettore Merlo, François Laviolette:
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review. CoRR abs/2107.12045 (2021) - [i2]Gabriel Laberge, Yann Pequignot, Foutse Khomh, Mario Marchand, Alexandre Mathieu:
Partial order: Finding Consensus among Uncertain Feature Attributions. CoRR abs/2110.13369 (2021) - 2019
- [i1]Gabriel Laberge, Shahrzad Shirzad, Patrick Diehl, Hartmut Kaiser, Serge Prudhomme, Adrian S. Lemoine:
Scheduling optimization of parallel linear algebra algorithms using Supervised Learning. CoRR abs/1909.03947 (2019)
Coauthor Index
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last updated on 2024-09-14 02:05 CEST by the dblp team
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