E-MAIL: {firstname}.{lastname} @

Short bio

Hi, I am associate professor at the Lamsade laboratory (Dauphine – PSL University), in Paris (France).

I am an active member of the MILES project and my research is about Machine Learning, Data Mining and Constraint Programming.

I am also co-director of the IASD Mater Program (AI Systems and Data Science), check it now if you are a student.


  • E-mail: firstname.lastname @
  • Mailing Address:
    • Place du Maréchal de Lattre de Tassigny,
    • 75 775 PARIS CEDEX 16, FRANCE
  • Office:
    • P407
  • Tel: +33 1 44 05 44 18



  • The Rasta Project: (Rasta for recognizing art style automatically). Online demo HERE.
  • NRPA: Parallel implementation of the NRPA search algorithm. HERE.
  • CPSM: A CP-based sequence miner that supports many constraints. More info HERE.
  • Dominance Programming Solver: A solver to evaluate DP expressions. More info HERE.
  • ParaMiner: A generic, parallel algorithm for closed pattern mining. More info HERE.
  • PLCM: A Fast parallel algorithm to mine closed frequent itemsets (based on lcm): HERE.
  • Runtime: A script to program and run experiments from the command line: HERE.
  • TetrisML: A Tetris clone in ML :) HERE.


[1] On the expressivity of bi-Lipschitz normalizing flows. Alexandre Verine, Benjamin Negrevergne, Fabrice Rossi, and Yann Chevaleyre. arXiv preprint arXiv:2107.07232, 2021. [ bib | http ]
[2] On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory. Alexandre Araujo, Benjamin Negrevergne, Yann Chevaleyre, and Jamal Atif. In Thirty-Fifth AAAI Conference on Artificial Intelligence - (AAAI), 2021. [ bib | http ]
[3] Advocating for Multiple Defense Strategies against Adversarial Examples. Alexandre Araujo, Laurent Meunier, Rafael Pinot, and Benjamin Negrevergne. In Workshop on Machine Learning for CyberSecurity - (MLCS@ECML-PKDD), 2020. [ bib | http ]
[4] Monte Carlo Graph Coloring. Tristan Cazenave, Benjamin Negrevergne, and Florian Sikora. In Workshop on Monte Carlo Search - (MCS@IJCAI), 2020. [ bib ]
[5] Understanding and Training Deep Diagonal Circulant Neural Networks. Alexandre Araujo, Benjamin Negrevergne, Yann Chevaleyre, and Jamal Atif. In The 24th European Conference on Artificial Intelligence - (ECAI), 2019. [ bib | .pdf ]
[6] Robust Neural Networks using Randomized Adversarial Training. Alexandre Araujo, Rafael Pinot, Benjamin Negrevergne, Laurent Meunier, Yann Chevaleyre, Florian Yger, and Atif Jamal. arXiv preprint arXiv:1903.10219, 2019. [ bib | http ]
[7] Training Compact Deep Learning Models for Video Classification using Circulant Matrices. Alexandre Araujo, Benjamin Negrevergne, Yann Chevaleyre, and Jamal Atif. In Workshop on YouTube-8M Large-Scale Video Understanding - (YouTube8M-@ECCV 2018), 2018. [ bib | http ]
[8] RASTA: Recognizing Art Style Automatically with Deep Learning. Adrian Lecoutre, Benjamin Negrevergne, and Florian Yger. In Asian Conference on Machine Learning - (ACML), 2017. [ bib | .pdf ]
[9] Distributed Nested Rollout Policy for Same Game. Benjamin Negrevergne and Tristan Cazenave. In Computer Games Workshop - (CGW@IJCAI), 2017. [ bib | .pdf ]
[10] Mining rare sequential patterns with ASP. Ahmed Samet, Thomas Guyet, and Benjamin Negrevergne. In International Conference on Inductive Logic Programming - (ILP), 2017. [ bib | http ]
[11] Modeling in MiningZinc. Anton Dries, Tias Guns, Siegfried Nijssen, Behrouz Babaki, Thanh Le Van, Benjamin Negrevergne, Sergey Paramonov, and Luc De Raedt. In Christian Bessiere, Luc De Raedt, Lars Kotthoff, Siegfried Nijssen, Barry O'Sullivan, and Dino Pedreschi, editors, Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach, pages 257–281. Springer International Publishing, Cham, 2016. [ bib | DOI | http ]
[12] Detecting strategic moves in HearthStone matches. Boris Doux, Clément Gautrais, and Benjamin Negrevergne. In Machine Learning and Data Mining for Sports Analytics - (MLDMSA@ECML/PKDD), 2016. [ bib | http | .pdf ]
[13] On declarative modeling of structured pattern mining [In press]. Tias Guns, Sergey Paramonov, and Benjamin Negrevergne. In DeLBP, Workshops at AAAI Conference on Artificial Intelligence, 2016. [ bib | .pdf ]
[14] Constraint-based sequence mining using constraint programming. Benjamin Negrevergne and Tias Guns. In Integration of AI and OR Techniques in Constraint Programming (CPAIOR), 2015. [ bib | arXiv ]
[15] PGLCM: efficient parallel mining of closed frequent gradual itemsets. TrongDinhThac Do, Alexandre Termier, Anne Laurent, Benjamin Negrevergne, Behrooz Omidvar-Tehrani, and Sihem Amer-Yahia. Knowledge and Information Systems (KAIS), pages 1–31, 2014. [ bib | DOI | http ]
[16] Dominance Programming for Itemset Mining. Benjamin Negrevergne, Anton Dries, Tias Guns, and Siegfried Nijssen. In International Conference on Data Mining (ICDM), 2013. [ bib | .pdf ]
[17] ParaMiner: a Generic Pattern Mining Algorithm for Multi-Core Architectures. Benjamin Negrevergne, Alexandre Termier, Marie-Christine Rousset, and Jean-François Mehaut. Journal of Data Mining and Knowledge Discovery (DMKD), 2013. Advance online publication. doi 10.1007/s10618-013-0313-2. [ bib | http ]
[18] Efficient Parallel Mining of Gradual Patterns on Multicore Processors. Anne Laurent, Benjamin Negrevergne, Nicolas Sicard, and Alexandre Termier. In Fabrice Guillet, Gilbert Ritschard, and Djamel Abdelkader Zighed, editors, Advances in Knowledge Discovery and Management, volume 398 of Studies in Computational Intelligence, pages 137–151. Springer Berlin Heidelberg, 2012. [ bib | DOI | http ]
[19] Discovering Closed Frequent Itemsets on Multicore: Parallelizing Computations and Optimizing Memory Accesses. Benjamin Negrevergne, Alexandre Termier, Jean-Francois Mehaut, and Takeaki Uno. In International Conference on High Performance Computing & Simulation (HPCS), pages 521–528, 2010. [ bib | .pdf ]
[20] PGP-mc: Towards a Multicore Parallel Approach for Mining Gradual Patterns. Anne Laurent, Benjamin Negrevergne, Nicolas Sicard, and Alexandre Termier. In Database Systems for Advanced Publications (DASFAA), pages 78–84, 2010. [ bib | .pdf ]
[21] A Generic and Parallel Pattern Mining Algorithm for Multi-Core Architectures. Benjamin Negrevergne. PhD thesis, University of Grenoble, 2011. [ bib | .pdf ]
[22] Découverte d'itemsets fréquents fermés sur architecture multicoeurs. Benjamin Negrevergne, Jean-Francois Méhaut, Alexandre Termier, and Takeaki Uno. In Extraction et Gestion des Connaissances (EGC), pages 465–470, 2010. [ bib | .pdf ]
[23] PGP-mc : extraction parallèle efficace de motifs graduels. Anne Laurent, Benjamin Negrevergne, Nicolas Sicard, and Alexandre Termier. In Extraction et Gestion des Connaissances (EGC), pages 453–464, 2010. [ bib ]
[24] ParaMiner: a Generic Parallel Pattern Mining Algorithm. Benjamin Negrevergne, Alexandre Termier, Marie-Christine Rousset, and Jean-François. Méhaut. Technical report, Laboratoire d'Informatique de Grenoble, 2011. [ bib | .pdf ]
[25] HLCM: a first experiment on parallel data mining with Haskell. Alexandre Termier, Benjamin Negrevergne, Simon Marlow, and Satnam Singh, 2011. [ bib ]

Date: 2013-04-21 Sun