  SOL is an open-source library for scalable online learning algorithms, and is
particularly suitable for learning with high-dimensional data. The library
provides a family of regular and sparse online learning algorithms for
large-scale binary and multi-class classification tasks with high efficiency,
scalability, portability, and extensibility. SOL was implemented in C++, and
provided with a collection of easy-to-use command-line tools, python wrappers
and library calls for users and developers, as well as comprehensive documents
for both beginners and advanced users. SOL is not only a practical machine
learning toolbox, but also a comprehensive experimental platform for online
learning research. Experiments demonstrate that SOL is highly efficient and
scalable for large-scale machine learning with high-dimensional data.
