3rd Place Winning Entry
Understanding high dimensional networks for continuous variables - The CSCS Algorithm
Syed Rahman worked on machine learning projects as an HPCC Systems intern in 2015 and 2016. He is a final year PhD student, studying Statistics at the University of Florida. The Convex Sparse Cholesky Selection algorithm can be used to show causal inferences between variables using a Directed Acyclic Graph (DAG). Syed was mentored by John Holt, who is the leader of the HPCC Systems machine learning library and Syed’s contribution is a valuable addition that will be appreciated by our users.
Read the blog featuring Syed’s work on the CSCS Algorithm and the work he previously completed on the CONCORD Algorithm if you want to find out more. You can also listen to presentations about these algorithms from our Engineering Summits in 2015 and 2016 (respectively).
Syed's prize winning poster presentation entered into our competition held on Community Day at the HPCC Systems Engineering Summit in 2016.