Event(s) on February 2021

• Wednesday, 3rd February, 2021

  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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