(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

  • 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.
  • 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]
  • S. Sidana, C. Laclau, M.R. Amini. Learning to Recommende Diverse Items over Implicit Feedback with Pandor. RecSys, 2018.
  • G. Balikas, C. Laclau, I. Redko, M.-R Amini. Cross-lingual Document Retrieval using Regularized Wasserstein Distance. ECIR, 2018.
  • C. Laclau, I. Redko, B. Mattei, Y. Bennani and V. Brault. Co-clustering through Optimal Transport. ICML, 2017.
    [paper][supplementary] [bibtex]
  • S. Sidana, C. Laclau, M.R. Amini, G. Vandelle and A. Bois-Crettez. KASANDR: A Large-Scale Dataset with Implicit Feedback for Recommendation. SIGIR, 2017
  • C. Laclau and M. Nadif. Diagonal Latent Block Model for Binary Data. Statistics and Computing, 2017
  • C. Laclau and M. Nadif. Hard and Fuzzy Diagonal Co-clustering for Document-Term Partitioning. Neurocomputing, 2016
  • C. Laclau and M. Nadif. Modèle de mélange parcimonieux pour la classification croisée et la sélection de variables. CAp 2016
  • C. Laclau. Hard and Fuzzy Block Clustering Algorithms for High Dimensional Data. PhD Thesis
  • C. Laclau and M. Nadif Diagonal Co-clustering Algorithm for Document-Word Partitioning. IDA, 2015
  • C. Laclau, Francisco de A.T. de Carvalho and M. Nadif. Fuzzy Co-clustering with Automated Variable Weighting. FUZZ-IEEE, 2015
  • C. Laclau and M. Nadif Fast Simultaneous Clustering and Feature Selection for Binary Data. IDA, 2014


Student Supervision

PhD Students

  • 2019 ... - Raphael Chevasson : Wasserstein embeddings for language model visualization and document clustering
    Co-supervised with Christophe Gravier - Excellence Scholarship from Institut Mines-Télécom
  • 2019 ... - Manvi Choudhary : Fairness in Graph Mining
    Co-supervised with Christine Largeron - ACADEMICS IDEX Scientific Breakthrough

Master Thesis

  • 2019 - Manvi Choudhary : Automated Fake News Detection with Machine Learning
  • 2019 - Ricardo I. Rojas : Graph Embedding for Heterogeneous Network (co-supervised with C. Largeron)
  • 2019 - Laetitia Couge : Extraction automatique de Connaissances de processus de fonctionnalisation de surface Hydrophobe par Laser femtoseconde

Former Student

  • PhD (2015/2018) - Sumit Sidana : Recommender Systems for Online Advertising (co-supervised with M.-R. Amini)


  • Vice president of the French Association on Machine Learning (SSFAM)
  • Co-responsible of ATLAS (supported by the GdR MADICS)