2018-2019: The list of dissertations topics on machine learning, deep-learning, and "model free" prediction will be available
this September.
2010-: Institut Mines-Télécom Atlantique, Brest,
lectures (in French) on nonstationary processes.
My 3^{rd} 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 deep learning and AI is added after reviewing a long series of papers and books (over 50 and counting) on these issues for
Mathematical Reviews®.
The writing of the book supporting these lectures is in progress.
List of lectures for the academic year 2018-2019:
Lecture 2 (Friday 11^{th} January 2019): Exponential GARCH model. Bootstrap methods and their application to model-free prediction and
inference of univariate models. Multivariate models. Change-point models.
Slides
Lecture 3 (Monday 25^{th} February 2019): Long-range dependent and multifractal volatility models.
Wavelet analysis of volatility processes.
Slides
Lecture 4 (Tuesday 26^{th} February 2019): Volatility estimation of high frequency time series.
Deep Learning. (TBA)
Slides
2009: Aarhus University, PhD lectures, based on the draft version of the book
Large Sample Inference for Long Memory
Processes (2012) Imperial College Press. In 2013, I wrote the review of this book for
Mathematical Reviews®.
If you are a MathSciNet subscriber, you could read this review from my author profile Additional material not covered in that book:
Slides
2006-2007: Ensae, lectures (in French) on
Long-range dependence and change-points, Applications
to univariate and multivariate financial time series,
1993-1996: Lectures on optimization techniques with Maple. I have typed a 200 pages document, that obviously needs to be upgraded.
Programming Resources
The first class requires a good working knowledge of R
Since the academic year 2016-2017, students undertaking their dissertation on Machine Learning, deep learning, etc., are using
Python
with the scikit-learn and
TensorFlow libraries.
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,
profiling, etc.
NLopt
is a free/open-source library for nonlinear optimization, callable from C,
C++, Fortran, Python, Julia,
ROctave, and Matlab programs.
Donald Knuth's home page. Don Knuth is the author of the celebrated books:
The Art of Computer Programming
You can find there everything which is important on semi-numerical and numerical algorithms,
T_{e}X etc.
BOINC,
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.
Other Teaching and Supervision Resources
Open Math Notes is a repository of freely downloadable mathematical works
in progress hosted by the American Mathematical Society
as a service to researchers, teachers and students.
MathJax is an open source Javascript library that uses
LaTeX
and MathML
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,
Pdf file.
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
Plagiarism.org:
This organization provides research institutes and academic places
with a database for deterring and detecting plagiarism.