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Title: | Ultra-sparse Matrix Normal Models of Multiway Data |
Speaker: | Prof Alfred Hero, University of Michigan, USA |
Time/Place: | 10:00 - 11:00 Zoom, (Meeting ID: 935 8469 3865) |
Abstract: | Modeling multi-way data is important for applications involving multi-indexed observables, e.g., hyperpsectral data that is indexed over spatial, frequency, and temporal dimensions. The sparse matrix normal model is a multivariate Gaussian representation that expresses the covariance matrix as a Kronecker product of sparse lower dimensional covariances. This model is equivalent to assuming the conditional dependencies of the covariates can be represented as a direct-product graph with few edges. We will present an alternative framework based on Cartesian product graph representation and Kronecker sums that leads to ultra-sparse and generative models for multi-way data. |
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