Publications

I am facing some difficulties to keep this up-to-date: you have more chances to have acess to my last publications on HAL.

Book Chapter

« Efficiency in the identification in the limit paradigm », Rémi Eyraud, Jeffrey Heinz, Ryo Yoshinaka, in Topics in Grammatical Inference, Jeffrey Heinz and José M. Sempere (Eds.), Springer, 2016, (personal version).

Journals

• International Journal of Molecular Science, « Tear nanoDSF Denaturation Profile Is Predictive of Glaucoma », Viktoriia Baksheeva, Veronika Tiulina, Elena Iomdina, Sergey Petrov, Olga Filippova, Nina Kushnarevich, Elena Suleiman, Rémi Eyraud, François Devred, Marina Serebryakova, Natalia Shebardina, Dmitry Chistyakov, Ivan Senin, Vladimir Mitkevich, Philipp Tsvetkov, and Evgeni Zernii, April 2023, (on-line version).
• Cancers, « Plasma nanoDSF Denaturation Profile at Baseline Is Predictive of Glioblastoma EGFR Status », Rémi Eyraud, Stéphane Ayache,Philipp O. Tsvetkov, Shanmugha Sri Kalidindi,Viktoriia E. Baksheeva,Sébastien Boissonneau,Carine Jiguet-Jiglaire, Romain Appay, Isabelle Nanni-Metellus, Olivier Chinot, François Devred, and Emeline Tabouret, January 2023, (online version).
• Machine Learning Journal, « Distillation of Weighted Automata from Recurrent Neural Networks using a Spectral Approach », Rémi Eyraud, Stéphane Ayache, April 2021, (on-line, authors’ version).
• Cancers, « An AI-powered blood test to detect cancer using nanoDSF », Philipp O. Tsvetkov, Rémi Eyraud, Stéphane Ayache, Anton A. Bougaev, Soazig Malesinski,  Hamed Benazha, Svetlana Gorokhova, Christophe Buffat, Caroline Dehais, Marc Sanson, Franck Bielle, Dominique Figarella Branger, Olivier Chinot, Emeline Tabouret, François Devred, March 2021, (online version).
• Fundamenta Informaticae, « Designing and Learning Substitutable Plane Graph Grammars », Rémi Eyraud, Jean-Christophe Janodet, Tim Oates, Frédéric Papadopoulos, November 2016, (submitted version).
• Transactions of the Association for Computational Linguistics, « Learning Strictly Local Subsequential Functions », Jane Chandlee, Rémi Eyraud, Jeffrey Heinz, November 2014, (online version, bibtex).
• Machine Learning Journal, « PAutomaC: a probabilistic automata and hidden Markov models learning competition », Sicco Verwer, Rémi Eyraud, Colin de la Higuera. July 2014, (authors’ version, mirror for the data).
• Journal of Machine Learning Research, « Using Contextual Representations to Efficiently Learn Context-Free Languages », Alexander Clark, Rémi Eyraud, Amaury Habrard. October 2010, (online version).
• Journal of Machine Learning Research, « Polynomial identification in the limit of context-free substitutable languages », Alexander Clark, Rémi Eyraud. August 2007 (on line version).
• Machine Learning Jounal, « LARS: a Learning Algorithm for Rewriting Systems », Rémi Eyraud, Colin de la Higuera, Jean-Christophe Janodet. January 2007 (on-line version)

Conferences

• MoL’19: « Learning with Partially Ordered Representations », Jane Chandlee, Remi Eyraud, Jeffrey Heinz, Adam Jardine, Jonathan Rawski, Proceedings of the 16th Meeting on the Mathematics of Language, (article, bibtex)
• ICGI’18: « Explaining black boxes on sequential data using weighted automata », Stéphane Ayache, Rémi Eyraud, Noé Goudian, 14th International Conference on Grammatical Inference, (article, python demo code)
• ICGI’16: « Sp2Learn: A Toolbox for the Spectral Learning of Weighted Automata », Denis Arrivault, Dominique, Benielli, François Denis, Rémi Eyraud, 13th International Conference on Grammatical Inference (article including bibtex)
• ICGI’16: « Results of the Sequence PredIction ChallengE (SPiCe): a Competition on Learning the Next Symbol in a Sequence », Borja Balle, Rémi Eyraud, Franco M. Luque, Ariadna Quattoni, Sicco Verwer, 13th International Conference on Grammatical Inference (article including bibtex)
• MoL’15: « Output Strictly Local Functions », Jane Chandlee, Rémi Eyraud, Jeffrey Heinz , 14th Meeting on the Mathematics of Language (.pdf, bibtex)
• ICGI’14: « Very efficient learning of structured classes of subsequential functions from positive data », Adam Jardine, Jane Chandlee, Rémi Eyraud, Jeffrey Heinz , The 12th International Colloquium on Grammatical Inference (.pdf).
• ICGI’12: « Learning Substitutable Binary Plane Graph Grammars », Rémi Eyraud, Jean-Christophe Janodet, Tim Oates , The 11th International Colloquium on Grammatical Inference (article including bibtex).
• ICGI’12: « Results of the PAutomaC Probabilistic Automaton Learning Competition « , Sicco Verwer, Rémi Eyraud, Colin de la Higuera , The 11th International Colloquium on Grammatical Inference (.pdf).
• ICGI’08: « A Polynomial Algorithm for the Inference of Context Free Languages », Alexander Clark, Rémi Eyraud, Amaury Habrard , The 9th International Colloquium on Grammatical Inference (.pdf).
• CoNLL’06: « Learning Auxiliary Fronting with Grammatical Inference », Alexander Clark, Rémi Eyraud The 10th Conference on Computational Natural Language Learning (.pdf).
• CogSci’06: « Learning Auxiliary Fronting with Grammatical Inference », Alexander Clark, Rémi Eyraud The 28th Annual Conference of the Cognitive Science Society, poster (.pdf).
• ALT’05: « Identification in the Limit of Substitutable Context-Free Languages », Alexander Clark, Rémi Eyraud The 16th International Conference on Algorithmic Learning Theory (.pdf).
• ICGI’04: « Representing Languages by Learnable Rewriting Systems », Rémi Eyraud, Colin de la Higuera, Jean-Christophe Janodet, 7th International Colloquium on Grammatical Inference(article).

Workshops, talks, posters

• Invited Talk (2018 Journées annuelles de Vérification, GdR IM), Spectral Learning of Weighted Automata, from theory to a toolbox, Rémi Eyraud.
• Invited Talk (2014 ELC Workshop on Learning Theory and Complexity), Efficiency bounds in the identification in the limit paradigm, Rémi Eyraud, (slides).
• Paper (EACL 2009 workshop on Computational Linguistic Aspects of Grammatical Inference, Athens, Greece, 2009), A note on contextual binary feature grammars, Alexander Clark, Rémi Eyraud, Amaury Habrard.
• Communication TML (workshop Teaching Machine Learning, Saint-Etienne, France, 2008), « Spring School in Machine Learning. Teaching experiences », with Cécile Capponi, François Denis, Amaury Habrard et Liva Ralaivola (pdf).
• Poster ML4NLP (workshop Machine Learning for Natural Languages Processing, Amsterdam, 2007) How to learn context-free grammars
• Poster Benelearn 2007 (Benelux machine learning conference, Amsterdam, 2007) Two methods to learn context-free languages
• Poster CAp’06 (Conférence en Apprentissage, TRégastel, 2006) Inférence grammaticale de langages hors-contextes
• Msc. report, « Inférence d’Automates par Fission d’Etats », 26th june 2003, Ecole des mines de Saint-Etienne (ps) (french only)

Habilitation à Diriger des Recherches

• HDR Learning Computational Models from Various Types of Structured Data, Rémi Eyraud defended the 19/07/2019 at Marseille (.pdf)

PhD thesis

• Thesis, Inférence Grammaticale de Langages Hors-Contextes, Rémi Eyraud defended the 22/11/2006 at Saint-Etienne (.pdf (french))