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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