Nonparametric statistics, computational statistics, clustering/quantization: theoretical and pratical aspects, software engineering, distributed computing, cloud computing (MS Azure)

Current position. Software engineer at eFront
Dec. 2008 - March 2012. Phd student with LSTA-Paris 6 and Lokad.
Supervisor: Gérard Biau.
Software engineer at Lokad.
2007-2008. Master 2: Probability, theory and applications. Paris 6.
2006-2007. "Agrégation de mathématiques".
2004-2008. Student at ENS Cachan (Dept. Maths Ker Lann) and Université Rennes 1.
2002-2004. "CPGE" Lycée Clémenceau Nantes.

2012 (defended on March 5th 2012) PhD Manuscript
Apprentissage à grande échelle: contribution à l'étude d' algorithmes de clustering répartis asynchrones.
Large scale learning: a contribution to distributed asynchronous clustering algorithms analysis.

2011 M. Durut, B. Patra and F. Rossi. A Discussion on Parallelization Schemes for Competitive Vector Quantization Algorithms.
ESANN 2012. Poster.

2011 B. Patra and M. Durut. CloudDALVQ project: large scale distributed asynchronous algorithms built on top of MS Azure. Open source project written in C#/.NET 4.0.

2010 B. Patra.Convergence of distributed asynchronous learning vector quantization algorithms.
Journal of Machine Learning Research, 2011, vol. 12.

2009. G. Biau, B. Patra.Sequential Quantile Prediction of Time Series.
IEEE Transactions on Information Theory, march 2011, vol. 57, n°3.
Download time series data set

February 2nd 2012. Theoreticals and practicals aspects of DALVQ algorithms.
GdR ISIS, Télécom ParisTech.

January 3rd 2012. Theoreticals aspects of DALVQ algorithms.
GT classification non supervisée, Université Paris-Orsay.

May 2011. Distributed asynchronous learning vector quantization algorithm
Télécom ParisTech.

March 2011. Distributed asynchronous learning vector quantization algorithm.
Seminar Parietal Team, INRIA Saclay.

January 2011. Distributed asynchronous learning vector quantization algorithm.
Groupe de Travail des Thésards, LPMA-LSTA Paris 6.

November 2010. Distributed asynchronous learning vector quantization algorithm.
Slides (full version (video embedded) and light version)
Séminaire SMILE, Ecole Normale Supérieure de Paris.

June 2010. Convergence of a distributed asynchronous learning vector quantization algorithm.
Groupe de Travail des Thésards, Lille.

June 2009. Non parametric sequential quantile prediction.
Journées dépendances, ENGREF Paris.

May 2009. Non parametric sequential quantile prediction.
41 ème journées de statistiques, Bordeaux. Slides.

April 2009. Implémentation de modèles d'agrégation d'experts.
Séminaire Bilbab, ENST-Paris EDF.

Colles MAPLE Lycée Saint Louis MP2 (2011)

Moniteur à l'Université Pierre et Marie Curie - Paris 6 (2008--2011)

2010-2011. LM 115 Suites et intégrales (MIME 24.1 Semestre 2) 36h.

2010-2011. LM 345 Probabilités (Section PIMA Semestre 1) 36 h.

2009-2010. LM125 Algèbre linéaire (3S Gr2 Semestre 2) 36 h.

2009-2010. LM125 Algèbre linéaire (MIME 16.4 Semestre 1) 36 h.

2008-2009. LM120 Calcul matriciel (Section IPCM Semestre 2) 42h.