For more information about this meeting, contact Mari Royer.
| Title: | Algebraic Models for Multilinear Dependence |
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| Seminar: | Job Candidate Talk |
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| Speaker: | Jason Morton |
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| Abstract: |
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| Abstract:
We discuss a new statistical technique inspired by research in tensor
geometry and
making use of cumulants, the higher order tensor analogs of the
covariance matrix. For
non-Gaussian data not derived from independent factors, tensor decomposition
techniques for factor analysis such as Principal Component Analysis
and Independent
Component Analysis are inadequate. Seeking a small, closed space of
models which is
computable and captures higher-order dependence leads to a proposed extension of
PCA and ICA, Principal Cumulant Component Analysis (PCCA). Estimation
is performed by maximization over a Grassmannian. |
Room Reservation Information
| Room Number: | MB114 |
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| Date: | 04 / 08 / 2009 |
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| Time: | 03:30pm - 04:30pm |
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