
<WRAP centeralign>##Statistical Machine Learning Seminar##\\ Hosted by Department of Mathematical Sciences</WRAP>

~~META:title=November 18, 2014~~
  * Date: Tuesday, November 18, 2014
  * Time: 12:00-1:00
  * Room: OW-100E
  * Speaker: Ming Yang (Computer Science)
  * Title: Multi-task Learning with Gaussian Matrix Generalized Inverse Gaussian Model


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<WRAP centeralign>**//Abstract//**</WRAP>

In this talk, we first introduce the multi-task learning problem and the application of Matrix Generalized Inverse Gaussian (MGIG) distribution to the problem. We still propose the GMGIG regression model for multi-task learning. To make the computation tractable, we simultaneously use variational inference and sampling techniques. In particular, we propose two sampling strategies for computing the statistics of the MGIG distribution.
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