2018-2019: The list of dissertations topics on machine learning, deep-learning, and "model free" prediction will be available
2010-: Institut Mines-Télécom Atlantique, Brest,
lectures (in French) on nonstationary processes.
My 3rd year lectures on nonstationary processes for the academic year 2018-2019 are updated.
The sections on change-point, spot volatility estimators, multifractality, computational statistics are modified, and
a new section on “big data” and AI is added after reviewing a long series of papers and books (over 50 and counting) on these issues for
The writing of the book supporting these lectures is in progress.
List of lectures for the academic year 2017-2018:
1993-1996: Lectures on optimization techniques with Maple. I have typed a 200 pages document, that obviously needs to be upgraded.
The classes require a good working knowledge of R
Since the academic year 2016-2017, students undertaking their dissertation on Machine Learning, deep learning, etc., are using
with the scikit-learn library.
The efficiency of the running of Python programs is substantially improved by calling
them within a Julia program.
Some statistical procedures are using Octave, a matrix oriented
programming language for numerical computing, the syntax of which is
similar to Matlab, up to some changes in the syntax of a few functions.
The C++ compiler of the GNU
Compiler Collection (GCC) is of great value. I'm using it since 1997. Valgrind is a useful tool for memory leak debugging,
is a free/open-source library for nonlinear optimization, callable from C,
C++, Fortran, Python, Julia,
ROctave, and Matlab programs.
the Berkeley Open Infrastructure for Network Computing, is an open-source software for volunteer and grid computing.
BOINC projects are covering several fields: physics, astronomy,
mathematics, biology, artificial intelligence, cryptography, computer science, etc. If your project is computationally very
intensive, and intellectually attractive, you can transform it into a BOINC project.
for displaying mathematics on webpages, which works on all modern browsers and that I'm
using for my web pages. Further details are provided by the paper published in the Notices of the American Mathematical SocietyMathJax: A Platform for Mathematics on the Web (2012), vol 59, 312-316,
The Scholarly Open Access website contains a critical analysis of
scholarly open-access publishing, and in particular provides a list of predatory journals and publishers that must be avoided.
Further details are given in J. Beall Predatory publishers are corrupting open access,
Nature 489, 179, (13 September 2012)DOI
This organization provides research institutes and academic places
with a database for deterring and detecting plagiarism.