How can we analyze real-world tensors where additional information is coupled with certain modes of tensors? The problem is effectively solved by coupled matrix-tensor factorization. There are many applications of coupled matrix-tensor factorization such as collaborative filtering, multi-way clustering, and link prediction. SCouT is a large-scale coupled matrix-tensor factorization algorithm running on the distributed Hadoop platform. By reusing intermediate data, carefully ordering computation, and transforming input matrix, SCouT significantly decreases the intermediate data and floating point operations.
The binary code of SCouT is available here.
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