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This is a port of mlpack/mlpack#401. There are some more details there. This is the original description from @stephentu:
Our SDP abstraction right now only supports sparse and dense matrices. This is sufficiently general, but for some certain classes of constraints, quite suboptimal.
As an example, suppose I want to have the constraint that the sum of all elements in the matrix is constant. While we can express this as Tr((11^T) * X) = b, this is quite inefficient to evaluate for something that could be expressed as X.sum().
Hence, it would be desirable to have a third type of constraint, "linearOperator", which is just a linear function which takes symmetric matrices to real numbers. The straightforward way to implement this would be a vector of std::function objects.
The text was updated successfully, but these errors were encountered:
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This is a port of mlpack/mlpack#401. There are some more details there. This is the original description from @stephentu:
The text was updated successfully, but these errors were encountered: