Model Selection for Optimal Prediction in Statistical Machine Learning (2020), vol 67,
155-168,
Machine Learning: Mathematical Theory and Scientific Applications (2019), vol 66,
1813-20,
From Decoupling and Self-Normalization to Machine Learning (2019), vol 66,
1641-46,
The Spring 2020 & 2021 lectures on deep learning by Yann LeCun at the NYU Center for Data Science.
The lectures on data science by Stéphane Mallat at the Collège de France.
Computer Science Resources
Donald Knuth's home page. Don Knuth is the author of the celebrated books:
The Art of Computer Programming
You can find there everything important on semi-numerical and numerical algorithms,
\(\TeX\) etc.
The C++
programming language is still the most powerful language. Valgrind is a useful tool for memory leak debugging,
profiling, etc.
NLopt
is a free/open-source library for nonlinear optimization,
The NISTStatistical
Reference Datasets (NIST StRD)
for assessing the numerical accuracy of statistical software packages. This
database is very useful for checking parts of statistical procedures.
Useful information on the issue of numerical accuracy of statistical software
packages is available at
B.D. McCullough's web page.