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Department of Engineering |
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University of Cambridge > Department of Engineering > Information Engineering > Computational and Biological Learning Lab > Sébastien Bratières |
I
am a member of the Machine
Learning group of the Cambridge University Engineering
Department, led by Zoubin
Ghahramani.
My research area is statistical machine learning. More specifically, I work on non-parametric Bayesian models, and try to implement learning algorithms for them in a distributed fashion (for instance using Hadoop). I am interested in applications to natural language processing, speech recognition, dialogue systems.
I received my “Ingénieur” degree from Ecole Centrale Paris, and an MPhil in Computer Speech and Language Processing from the University of Cambridge in 2001. I have been working in the speech industry ever since, and started my PhD on a part-time basis in 2009. In my professional life, I am the resident Speech Evangelist at dawin, a German company which produces embedded speech recognition solutions for the logistics industry.
September 2010: I received another AWS in Education Research Grant for my project A large-scale infinite HMM trained on raw text. This grant comes as a credit towards Amazon Web Services, such as Amazon Elastic Compute Cloud.
August 2010: I have just been awarded the Yahoo! Key Scientfic Challenge Award in the machine learning area. Here is the press release.
August 2009: Jurgen van Gael, Andreas Vlachos and I received an AWS in Education Research Grant to carry out work with Elastic MapReduce, Elastic Compute Cloud, and Simple Storage Service, with the infinite HMM.
Sébastien Bratières, Jurgen van Gael, Andreas
Vlachos, Zoubin Ghahramani (2010)
Scaling the iHMM:
Parallelization versus Hadoop
Workshop on Scalable Machine
Learning and Applications, IEEE International Conference on
Computing and Information Technology, Bradford, UK
Sébastien Bratières, Jurgen van Gael, Andreas
Vlachos, Zoubin Ghahramani (2010)
Learning the iHMM through
iterative map-reduce
Poster at Thirteenth International
Conference on Artificial Intelligence and Statistics (AISTATS 2010).
Errata in scientific books and publications are clearly a plague, especially for self-learners. When I read a scientific book, I collect errata; here I will post some of my errata lists, for the benefit of the readership.
Errata for Kevin Murphy (2012), Machine Learning, a Probabilistic Perspective.
E-mail: sb358 usual-symbol cam dot
ac and then dot uk
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© University
of Cambridge, Department of Engineering
Information provided by
Sébastien
Bratières
