[ https://issues.apache.org/jira/browse/FLINK-1718?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Till Rohrmann reassigned FLINK-1718: ------------------------------------ Assignee: Till Rohrmann > Add sparse vector and sparse matrix types to machine learning library > --------------------------------------------------------------------- > > Key: FLINK-1718 > URL: https://issues.apache.org/jira/browse/FLINK-1718 > Project: Flink > Issue Type: New Feature > Components: Machine Learning Library > Reporter: Till Rohrmann > Assignee: Till Rohrmann > Labels: ML > > Currently, the machine learning library only supports dense matrix and dense > vectors. For future algorithms it would be beneficial to also support sparse > vectors and matrices. > I'd propose to use the compressed sparse column (CSC) representation, because > it allows rather efficient operations compared to a map backed sparse > matrix/vector implementation. Furthermore, this is also the format the Breeze > library expects for sparse matrices/vectors. Thus, it is easy to convert to a > sparse breeze data structure which provides us with many linear algebra > operations. > BIDMat [1] uses the same data representation. > Resources: > [1] [https://github.com/BIDData/BIDMat] -- This message was sent by Atlassian JIRA (v6.3.4#6332)