(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 of my courses.

Book/Theses   Journal articles   Conference papers   Informal publications

  • I. Redko, C. Laclau. On Fair Cost Sharing Games in Machine Learning. To appear in AAAI, 2019.
  • C. Laclau and V. Brault. Noise-free Latent Block Model for High Dimensional Data. Data Mining and Knowledge Discovery, 2018
    [paper][codes 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