2021 Feb     Mar     Apr     May     Jun     Jul     Aug    
2020 Jan     May     Jun     Jul     Aug     Sep     Oct     Nov     Dec    
2019 Jan     Feb     Mar     Apr     May     Jun     Jul     Aug     Oct     Nov    
2018 Jan     Feb     Mar     Apr     May     Jun     Jul     Aug     Oct     Nov     Dec    
2017 Jan     Feb     Mar     Apr     May     Jun     Jul     Aug     Oct     Nov     Dec    

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.



All years