Accelerating a Distributed CPD Algorithm for Large Dense, Skewed Tensors
BigData, pp. 408-417, 2018.
Canonical Polyadic Decomposition (CPD) is a powerful technique for uncovering multilinear relationships in tensors. Current research in scalable CPD has focused on designing efficient decomposition algorithms for large sparse tensors that arise in machine learning and data mining applications. This work addresses the complementary need fo...More
Full Text (Upload PDF)
PPT (Upload PPT)