[jira] [Created] (FLINK-1718) Add sparse vector and sparse matrix types to machine learning library

["Till Rohrmann (JIRA)" <ji...@apache.org>]

Till Rohrmann created FLINK-1718:
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             Summary: 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: Improvement
            Reporter: Till Rohrmann


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.



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