Publications

Conferences

• 📄 Fairness in job recommendations: estimating, explaining, and reducing gender gaps by Guilaume Bied, Christophe Gaillac, Morgane Hoffmann, Elia Perennes, Philippe Caillou, Bruno Crepon, Solal Nathan and Michèle Sebag, ECAI, AEQUITAS Workshop ( 📄 Slides), 2023.
• 📄 Toward Job Recommendation for All, by Guilaume Bied, Solal Nathan, Elia Perennes, Morgane Hoffmann, Philippe Caillou, Bruno Crepon, Christophe Gaillac and Michèle Sebag, IJCAI (AI And Social Good Track) ( 📄 Poster, 📄 Slides, Code), 2023. Also presented at ECML PKDD, AI4HR Workshop, 2023.
• 📄 RECTO : Recommandation d’Emploi diminuant la Congestion par Transport Optimal, by Guilaume Bied, Elia Perennes, Solal Nathan, Victor Alfonso Naya, Philippe Caillou, Bruno Crepon, Christophe Gaillac and Michèle Sebag, APIA [Best Paper Award], 2023.
• 📄 Recommender system in a non-stationary context: recommending job ads in pandemic times, by Guillaume Bied, Solal Nathan, Elia Perennes, Victor Alfonso Naya, Philippe Caillou, Bruno Crepon, Christophe Gaillac and Michèle Sebag, presented at ECML PKDD ( 📄 Poster), 2022.
• 📄 On the impact of overfitting in learning to rank using a margin loss: a case study in job recommender systems by Guillaume Bied and Solal Nathan, poster presented at Baylearn and JDSE the same year ( 📄 Poster), 2022.

Scientific mediation

• Introduction à l’Apprentissage Automatique, Revue 3EI, 2022
• Word Embedding Introduction, Revue 3EI, 2022

Internship reports

• M2 Internship: 📄 Combatting Unemployment: Data, Recommendations and Fairness, 2022.
• ARPE: 📄 3D Reconstruction using Implicit Function Methods: PiFU, NeRF, Novel View Synthesis, Neural Rendering and more presented as a 📄 Poster, 2021.
• M1 Internship: 📄 Differential Privacy applied to Crowd Density Estimation, presented as a 📄 Poster, 2020.