  LIBS2ML is a library based on scalable second order learning algorithms for
solving large-scale problems, i.e., big data problems in machine learning.
LIBS2ML has been developed using MEX files, i.e., C++ with MATLAB/Octave
interface to take the advantage of both the worlds, i.e., faster learning using
C++ and easy I/O using MATLAB. Most of the available libraries are either in
MATLAB/Python/R which are very slow and not suitable for large-scale learning,
or are in C/C++ which does not have easy ways to take input and display
results. So LIBS2ML is completely unique due to its focus on the scalable
second order methods, the hot research topic, and being based on MEX files.
Thus it provides researchers a comprehensive environment to evaluate their
ideas and it also provides machine learning practitioners an effective tool to
deal with the large-scale learning problems. LIBS2ML is an open-source, highly
efficient, extensible, scalable, readable, portable and easy to use library.
The library can be downloaded from the URL:
\url{https://github.com/jmdvinodjmd/LIBS2ML}.
