Research activities


My main research domain is machine learning and my interests include:

  • Metric and Similarity Learning
    I co-authored a book with Aurélien Bellet and Marc Sebban, have a look!
  • Domain Adaptation and Transfer Learning
  • Learning theory
  • Fraud and anomaly detection
  • Grammatical inference and Spectral Learning
  • Online learning

Current and past projects

Reviewing activities

  • Reviewer/Program committee member: NeurIPS 2019 (Area Chair), IJCAI 2019 (Senior PC), ICML 2019 (top reviewer award), AISTATS 2019, ICLR 2019, NeurIPS 2018 (top reviewer award), IJCAI 2018 (Senior PC, award), ICML 2018 (top reviewer award), AISTATS 2018, ICLR 2018, AAAI 2018, NIPS 2017, IJCAI 2017 (Senior PC), ICML 2017, AISTATS 2017, NIPS 2016, ICGI 2016, ICML 2016, AISTATS 2016, NIPS 2015, ICML 2015 (reviewer award), LMCE (workshop) 2015-2014, CAp 2013-2014-2015-2016, IJCAI 2013, ICPRAM 2015-2012, IJCNLP 2013, IbPRIA 2013, LAFLang (workshop) 2013-2011, ECML/PKDD 2010, ECAI 2010, ICML 2009, ICGI 2008, ICML 2008, ICDM 2007, ADMA 2005, ECML/PKDD 2003-2004
  • Reviewer for International journals: Journal of Machine Learning Research, Machine Learning Journal, International Journal for Computer Vision, Knowledge and Information Systems, Fundamental Informaticae, Theoretical Computer Science, Neural Computing and Applications

Some events I have been involved in

PhD students

  • Julien Tissier, on Binary Representation Learning for Semantic Similarities (Starting data october 2016)
  • Jordan Frery, on Ensemble Methods for fraud Detection (CIFRE with WORLDLINE, starting data January 2016)
  • Guillaume Metzler, on Outlier detection and fraudster profile identification in bank fraud analysis (CIFRE with BLITZ, starting data January 2016)
  • Michael Perrot, on Metric learning methods.
  • Mattias Gybels, on Spectral Learning of weighted automata.
  • Jean-Philippe Peyrache, New Iterative Approaches with Theoretical Guarantees for Unsupervised Domain Adaptation (PhD defended in July 2014)
  • Emilie Morvant, Learning majority votes for supervised classification and domain adaptation: PAC-Bayesian approaches and similarity combinations. (PhD defended in September 2013, Emilie received a runner-up best PhD award in Artificial Intelligence from AFIA and a Phd award from Aix-Marseille University)
  • Aurelien Bellet, Supervised Metric Learning with Generalization Guarantees (PhD defended in December 2012, Aurélien received the AFIA best PhD award in Artificial Intelligence for his work.)
  • Laurent Boyer, Probabilistic Learning of Edit Similarities (PhD defended in March 2011)