Amaury Habrard's Homepage

International Journals

JMLR "Using Contextual Representations to Efficiently Learn Context-Free Languages."
Alexander Clark, Rémi Eyraud and Amaury Habrard.
Journal of Machine Learning Research, vol 11, p2707-2744, 2010. (online version)
PR "Learning probabilistic models of tree edit distance."
Laurent Boyer, Marc Bernard, Amaury Habrard and Marc Sebban.
Pattern Recognition, Vol 41, n8, p2611-2629, 2008. Elsevier Science.
FI "Detecting Irrelevant Subtrees to Improve Probabilistic Learning from Tree-structured Data."
Amaury Habrard, Marc Bernard and Marc Sebban.
Fundamenta Informaticae: Special Issue on Mining Graphs, Trees and Sequences, Vol 66, n1-2, p103-130, 2005. IOS Press. (bibtex, draft .ps).

International Conferences

ALT'10 "A Spectral Approach for Probabilistic Grammatical Inference on Trees"
Raphael Bailly, Amaury Habrard and François Denis.
21th International Conference on Algorithmic Learning Theory, LNCS 6331, p74-88, 2010.
ICTAI'09 "Learning Constrained Edit State Machines"
Laurent Boyer, Olivier Gandrillon, Amaury Habrard, Mathilde Pellerin and Marc Sebban.
21st International Conference on Tools with Artificiel Intelligence, p734-741, 2009.
CLAGI'09 "A note on contextual binary feature grammars"
Alexander Clark, Rémi Eyraud and Amaury Habrard.
ACL 2009 workshop on Computational Linguistic Aspects of Grammatical Inference, p33-40, 2009.
SSPR'08 "Melody Recognition with Learned Edit Distances"
Amaury Habrard, Jose-Manuel Inesta, David Rizo, Marc Sebban
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshops, SSPR 2008 and SPR 2008, p86-96, Volume 5342 of LNCS, Springer.
ICGI'08 "A Polynomial Algorithm for the Inference of Context Free Languages"
Alexander Clark, Rémi Eyraud and Amaury Habrard.
9th International Colloquium on Grammatical Inference, p29-42, Volume 5278 of LNCS, Springer.
ICGI'08 "Relevant Representations for the Inference of Rational Stochastic Tree Languages"
François Denis, Edouard Gilbert, Amaury Habrard, Faissal Ouardi and Marc Tommasi.
9th International Colloquium on Grammatical Inference, p57-70, Volume 5278 of LNCS, Springer.
ECML'08 "SEDiL: Software for Edit Distance Learning"
Laurent Boyer, Yann Esposito, Amaury Habrard, Jose Oncina and Marc Sebban.
19th European Conference on Machine Learning , p672-677, Volume 5212 of LNCS, Springer (draft pdf).
ALT'07 "Learning rational stochastic tree languages"
François Denis and Amaury Habrard.
19th International Conference on Algorithmic Learning Theory, p242-256, 2007, Volume 4754 of LNCS, Springer. LNCS.( draft .pdf )
ECML'07 "Learning Metrics between Tree Structured Data: Application to Image Recognition."
Laurent Boyer, Amaury Habrard and Marc Sebban.
18th European Conference on Machine Learning, p54-66, 2007, Volume 4701 of LNCS, Springer. LNCS. ( draft .pdf )
ICGI'06 "Using Pseudo-stochastic Rational Languages in Probabilistic Grammatical Inference"
Amaury Habrard, François Denis and Yann Esposito.
8th International Colloquium on Grammatical Inference, p112-124, 2006, Volume 4201 of LNCS, Springer 2006. LNCS. ( extended draft version with annex .pdf, report)
ICGI'06 "Learning multiplicity tree automata"
Amaury Habrard and Jose Oncina.
8th International Colloquium on Grammatical Inference. p268-280, 2006, Volume 4201 of LNCS, Springer. LNCS. ( draft .pdf)
ECML'06 "Learning Stochastic Tree Edit Distance"
Marc Bernard, Amaury Habrard and Marc Sebban.
17th European Conference on Machine Learning, p42-52, 2006, Volume 4212 of LNCS, Springer. LNCS. ( draft .pdf )
COLT'06 "Learning rational stochastic languages"
François Denis, Yann Esposito and Amaury Habrard.
19th Annual Conference on Learning Theory, p274-288, 2006, Volume 4005 of LNCS, Springer. LNCS.( draft .pdf )
FLAIRS'05 "Correction of Uniformly Noisy Distributions to Improve Probabilistic Grammatical Inference Algorithms"
Amaury Habrard, Marc Bernard and Marc Sebban.
18th International Florida Artificial Intelligence Research Society Conference. p493-498, May 2005. AAAI Press.(bibtex, draft .pdf)
ECML'03 "Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference"
Amaury Habrard, Marc Bernard and Marc Sebban.
14th European Conference on Machine Learning. LNAI 2837, p169-180, 2003. (bibtex, .ps, .pdf)
AIME'03 "Multi-Relational Data Mining of Medical Databases"
Amaury Habrard, Marc Bernard and François Jacquenet.
9th Conference on Artificial Intelligence for Medicine Europe. LNAI 2780, p365-374, 2003. (postscript, pdf, bibtex)
MGTS'03 "Probabilistic Approach for Reduction of Irrelevant Tree-structured Data"
Amaury Habrard, Marc Bernard and Marc Sebban.
1st International Workshop on Mining Graphs Trees and Sequences (co-located with ECML/PKDD-2003), p11-20, 2003. (bibtex, .ps, .pdf)
ICGI'02 "Generalized Stochastic Tree Automata for Multi-Relational Data Mining"
Amaury Habrard, Marc Bernard and François Jacquenet.
6th International Colloquium on Grammatical Inference. LNAI 2484, p120-133, 2002. (postscript, pdf, bibtex)
PKDD'02 Discovery Challenge "Mining Probabilistic Tree Patterns in a Medical Database"
Amaury Habrard, Marc Bernard and François Jacquenet.
PKDD'02 Discovery Challenge on chronic hepatitis (postscript, pdf).
WIP-ILP'01 "Learning Stochastic Logic Programs"
Marc Bernard and Amaury Habrard.
Work-in-Progress track at the 11th International Conference on Inductive Logic Programming, p19-26, 2001. (postscript, bibtex)

National Conferences

CAP'08 "Learning string edit similarities using constrained finite state machines"
Laurent Boyer, Amaury Habrard, Fabrice Muhlenbach, Marc Sebban
Conférence d'Apprentissage
CAP'06 "Inférence des langages stochastiques rationnels"
François Denis, Yann Esposito, Amaury Habrard.
Conférence d'Apprentissage (pdf, bibtex)
CAP'04 "Correction de distributions statistiques uniformément bruitées en vue d'améliorer les algorithmes d'inférence grammaticale probabiliste"
Amaury Habrard, Marc Bernard and Marc Sebban.
Conférence d'Apprentissage (postscript, pdf, bibtex)
CAP'03 "Approche Probabiliste pour la Réduction de Sous-Arbres Bruités"
Amaury Habrard, Marc Bernard and Marc Sebban.
Conférence d'Apprentissage (postscript, bibtex)
CAP'02 "Apprentissage d'Automates d'Arbres Stochastiques Généralisés à partir de Bases de Données Relationnelles"
Amaury Habrard, Marc Bernard and François Jacquenet.
Conférence d'Apprentissage (postscript, bibtex)
CAP'01 "Inférence de Programmes Logiques Stochastiques"
Marc Bernard and Amaury Habrard.
Conférence d'Apprentissage (postscript, bibtex)

PhD Thesis

PhD Thesis "Models and Techniques in Probabilistic Grammatical Inference: Dealing with Noisy Data and Knowledge Discovery." Amaury Habrard. PhD Thesis, University of Saint-Etienne, October 2004. (available in french: PDF file, gzipped Postscript, Bibtex, slides)

Talks/Seminars

Talk Models and Techniques for Dealing with Noisy Data in Probabilistic Grammatical Inference Amaury Habrard. University of Alicante, March 2006. Slides pdf.
Talk "Handling Noisy Data in Machine Learning from Semi-structured Data" Amaury Habrard. Mostrare Workshop on Learning Tree Languages. Lille, 17 december 2003. Slides (pdf).

	Amaury Habrard 's home page
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Home	International Journals JMLR "Using Contextual Representations to Efficiently Learn Context-Free Languages." Alexander Clark, Rémi Eyraud and Amaury Habrard. Journal of Machine Learning Research, vol 11, p2707-2744, 2010. (online version) PR "Learning probabilistic models of tree edit distance." Laurent Boyer, Marc Bernard, Amaury Habrard and Marc Sebban. Pattern Recognition, Vol 41, n8, p2611-2629, 2008. Elsevier Science. FI "Detecting Irrelevant Subtrees to Improve Probabilistic Learning from Tree-structured Data." Amaury Habrard, Marc Bernard and Marc Sebban. Fundamenta Informaticae: Special Issue on Mining Graphs, Trees and Sequences, Vol 66, n1-2, p103-130, 2005. IOS Press. (bibtex, draft .ps). International Conferences ALT'10 "A Spectral Approach for Probabilistic Grammatical Inference on Trees" Raphael Bailly, Amaury Habrard and François Denis. 21th International Conference on Algorithmic Learning Theory, LNCS 6331, p74-88, 2010. ICTAI'09 "Learning Constrained Edit State Machines" Laurent Boyer, Olivier Gandrillon, Amaury Habrard, Mathilde Pellerin and Marc Sebban. 21st International Conference on Tools with Artificiel Intelligence, p734-741, 2009. CLAGI'09 "A note on contextual binary feature grammars" Alexander Clark, Rémi Eyraud and Amaury Habrard. ACL 2009 workshop on Computational Linguistic Aspects of Grammatical Inference, p33-40, 2009. SSPR'08 "Melody Recognition with Learned Edit Distances" Amaury Habrard, Jose-Manuel Inesta, David Rizo, Marc Sebban Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshops, SSPR 2008 and SPR 2008, p86-96, Volume 5342 of LNCS, Springer. ICGI'08 "A Polynomial Algorithm for the Inference of Context Free Languages" Alexander Clark, Rémi Eyraud and Amaury Habrard. 9th International Colloquium on Grammatical Inference, p29-42, Volume 5278 of LNCS, Springer. ICGI'08 "Relevant Representations for the Inference of Rational Stochastic Tree Languages" François Denis, Edouard Gilbert, Amaury Habrard, Faissal Ouardi and Marc Tommasi. 9th International Colloquium on Grammatical Inference, p57-70, Volume 5278 of LNCS, Springer. ECML'08 "SEDiL: Software for Edit Distance Learning" Laurent Boyer, Yann Esposito, Amaury Habrard, Jose Oncina and Marc Sebban. 19th European Conference on Machine Learning , p672-677, Volume 5212 of LNCS, Springer (draft pdf). ALT'07 "Learning rational stochastic tree languages" François Denis and Amaury Habrard. 19th International Conference on Algorithmic Learning Theory, p242-256, 2007, Volume 4754 of LNCS, Springer. LNCS.( draft .pdf ) ECML'07 "Learning Metrics between Tree Structured Data: Application to Image Recognition." Laurent Boyer, Amaury Habrard and Marc Sebban. 18th European Conference on Machine Learning, p54-66, 2007, Volume 4701 of LNCS, Springer. LNCS. ( draft .pdf ) ICGI'06 "Using Pseudo-stochastic Rational Languages in Probabilistic Grammatical Inference" Amaury Habrard, François Denis and Yann Esposito. 8th International Colloquium on Grammatical Inference, p112-124, 2006, Volume 4201 of LNCS, Springer 2006. LNCS. ( extended draft version with annex .pdf, report) ICGI'06 "Learning multiplicity tree automata" Amaury Habrard and Jose Oncina. 8th International Colloquium on Grammatical Inference. p268-280, 2006, Volume 4201 of LNCS, Springer. LNCS. ( draft .pdf) ECML'06 "Learning Stochastic Tree Edit Distance" Marc Bernard, Amaury Habrard and Marc Sebban. 17th European Conference on Machine Learning, p42-52, 2006, Volume 4212 of LNCS, Springer. LNCS. ( draft .pdf ) COLT'06 "Learning rational stochastic languages" François Denis, Yann Esposito and Amaury Habrard. 19th Annual Conference on Learning Theory, p274-288, 2006, Volume 4005 of LNCS, Springer. LNCS.( draft .pdf ) FLAIRS'05 "Correction of Uniformly Noisy Distributions to Improve Probabilistic Grammatical Inference Algorithms" Amaury Habrard, Marc Bernard and Marc Sebban. 18th International Florida Artificial Intelligence Research Society Conference. p493-498, May 2005. AAAI Press.(bibtex, draft .pdf) ECML'03 "Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference" Amaury Habrard, Marc Bernard and Marc Sebban. 14th European Conference on Machine Learning. LNAI 2837, p169-180, 2003. (bibtex, .ps, .pdf) AIME'03 "Multi-Relational Data Mining of Medical Databases" Amaury Habrard, Marc Bernard and François Jacquenet. 9th Conference on Artificial Intelligence for Medicine Europe. LNAI 2780, p365-374, 2003. (postscript, pdf, bibtex) MGTS'03 "Probabilistic Approach for Reduction of Irrelevant Tree-structured Data" Amaury Habrard, Marc Bernard and Marc Sebban. 1st International Workshop on Mining Graphs Trees and Sequences (co-located with ECML/PKDD-2003), p11-20, 2003. (bibtex, .ps, .pdf) ICGI'02 "Generalized Stochastic Tree Automata for Multi-Relational Data Mining" Amaury Habrard, Marc Bernard and François Jacquenet. 6th International Colloquium on Grammatical Inference. LNAI 2484, p120-133, 2002. (postscript, pdf, bibtex) PKDD'02 Discovery Challenge "Mining Probabilistic Tree Patterns in a Medical Database" Amaury Habrard, Marc Bernard and François Jacquenet. PKDD'02 Discovery Challenge on chronic hepatitis (postscript, pdf). WIP-ILP'01 "Learning Stochastic Logic Programs" Marc Bernard and Amaury Habrard. Work-in-Progress track at the 11th International Conference on Inductive Logic Programming, p19-26, 2001. (postscript, bibtex) National Conferences CAP'08 "Learning string edit similarities using constrained finite state machines" Laurent Boyer, Amaury Habrard, Fabrice Muhlenbach, Marc Sebban Conférence d'Apprentissage CAP'06 "Inférence des langages stochastiques rationnels" François Denis, Yann Esposito, Amaury Habrard. Conférence d'Apprentissage (pdf, bibtex) CAP'04 "Correction de distributions statistiques uniformément bruitées en vue d'améliorer les algorithmes d'inférence grammaticale probabiliste" Amaury Habrard, Marc Bernard and Marc Sebban. Conférence d'Apprentissage (postscript, pdf, bibtex) CAP'03 "Approche Probabiliste pour la Réduction de Sous-Arbres Bruités" Amaury Habrard, Marc Bernard and Marc Sebban. Conférence d'Apprentissage (postscript, bibtex) CAP'02 "Apprentissage d'Automates d'Arbres Stochastiques Généralisés à partir de Bases de Données Relationnelles" Amaury Habrard, Marc Bernard and François Jacquenet. Conférence d'Apprentissage (postscript, bibtex) CAP'01 "Inférence de Programmes Logiques Stochastiques" Marc Bernard and Amaury Habrard. Conférence d'Apprentissage (postscript, bibtex) PhD Thesis PhD Thesis "Models and Techniques in Probabilistic Grammatical Inference: Dealing with Noisy Data and Knowledge Discovery." Amaury Habrard. PhD Thesis, University of Saint-Etienne, October 2004. (available in french: PDF file, gzipped Postscript, Bibtex, slides) Talks/Seminars Talk Models and Techniques for Dealing with Noisy Data in Probabilistic Grammatical Inference Amaury Habrard. University of Alicante, March 2006. Slides pdf. Talk "Handling Noisy Data in Machine Learning from Semi-structured Data" Amaury Habrard. Mostrare Workshop on Learning Tree Languages. Lille, 17 december 2003. Slides (pdf).
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