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Computationally Efficient CP Tensor Decomposition Update Framework for Emerging Component Discovery in Streaming Data
Pierre-David Letourneau, Muthu Baskaran, Tom Henretty, James Ezick, Richard Lethin
09/25/2018Publication Source: 2018 IEEE High Performance Extreme Computing Conference (HPEC '18), Waltham, MA, USA [Best Paper Award]
09/25/2018Publication Source: 2018 IEEE High Performance Extreme Computing Conference (HPEC '18), Waltham, MA, USA [Best Paper Award]
We present streaming CP update, an algorithmic framework for updating CP tensor decompositions that possesses the capability of identifying emerging components and can produce decompositions of large, sparse tensors streaming along multiple modes at a low computational cost. We discuss a large-scale implementation of the proposed scheme integrated within the ENSIGN tensor analysis package, and we evaluate and demonstrate the performance of the framework, in terms of computational efficiency and capability to discover emerging components, on a real cyber dataset.
