Publications
(You may also look at my Google Scholar and dblp profiles). I'm also currently updating my Github where you can find some of the code for the following articles and the resources for my courses.
■ Book/Theses ■ Journal articles ■ Conference papers ■ Informal publications
Under Review
- P. Krzakala, J. Yang, R. Flamary, F. d'Alché-Buc, C. Laclau, M. Labeau End-to-end Supervised Prediction of Arbitrary-size Graphs with Partially-Masked Fused Gromov-Wasserstein Matching.
- V. Brault, E. Devijver and C. Laclau. Mixture of segmentation for heterogeneous functional data.
- C. Laclau, C. Largeron and M. Choudhary. A Survey on Fairness for Machine Learning on Graphs. under review, available on arxiv
Latest Publications
- F. Torba, C. Gravier, C. Laclau, A. Kammoun, J. Subercaze A Study on Hierarchical Text Classification as a Seq2seq Task. ECIR, 2024.
- A. Gourru, C. Laclau, M. Choudhary, and C. Largeron. Variational Perspective on Fair Edge Prediction. IDA, 2024
- T. Leteno, A. Gourru, C. Laclau, C. Gravier Fair Text Classification with Wasserstein Independence. EMNLP, 2023.
- J. Tissier, C. Laclau. Understanding the Benefits of Forgetting when Learning on Dynamic Graphs. ECML-PKDD, 2022.
- A. Burashnikova, M. Clausel, C. Laclau, F. Iutzeler, Y. Maximov, M-R. Amini. Learning over no-Preferred and Preferred Sequence of items for Robust Recommendation. Journal of Artificial Intelligence Research, 2021
- S. Sidana, M. Trofimov, O. Horodnytskyi, C. Laclau, Y. Maximov, M-R. Amini. User preference and embedding learning with implicit feedback for recommender systems. Data Mining and Knowledge Discovery, 2021
- N. Vesseron, I. Redko, C. Laclau. Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond. AISTAT, 2021.
- C. Laclau., I. Redko, M. Choudhary, C. Largeron. All of the Fairness for Edge Prediction with Optimal Transport. AISTAT, 2021.
[paper][supplementary][code] - I. Redko, C. Laclau. On Fair Cost Sharing Games in Machine Learning. AAAI, 2019.
- C. Laclau and V. Brault. Noise-free Latent Block Model for High Dimensional Data. Data Mining and Knowledge Discovery, 2018
[paper][code and data]
Other
Student Supervision
PhD Students
- 2023 ... - Paul Krzakala: Optimal transport distance for modeling graph dynamics
Co-supervised with F. d'Alche-Buc and Remi Flamary. - 2023 ... - Mathilde Perez: Fairness in Temporal Graphs
Co-supervised with F. d'Alche-Buc. - 2022 ... - Richard Serrano: Machine Learning on Imperfect Graphs
Co-supervised with C. Largeron and B. Jeudy. - 2022 ... - Thibaud Leteno: Bias and fairness in compressed language models
Co-supervised with Christophe Gravier and Antoine Gourru - ANR Diké - 2019 ... - Raphael Chevasson : Exploring the Potential of
Free-Order Generation Language Models
Co-supervised with Christophe Gravier - Excellence Scholarship from Institut Mines-Télécom
Former Student
- PhD (2015/2018) - Sumit Sidana : Recommender Systems for Online Advertising (co-supervised with M.-R. Amini)
Responsibilities