Accelerated Sampling for the Indian Buffet Process. Finale Doshi-Velez and Zoubin Ghahramani ICML 2009 Presented by: John Paisley, Duke University. Introduction.
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Finale Doshi-Velez and Zoubin Ghahramani
Presented by: John Paisley, Duke University
This prior can be used for the linear-Gaussian model, to infer the number of underlying vectors that are linearly combined to construct a matrix.
and for new features as,
which significantly increases the amount of computation that needs to be done to calculate the likelihood.
We can efficiently compute means and covariances with data removed,
And then efficiently update the mean and covariance using all data using the statistics for the window.
And rank-one updates can be used when updating
Generate a linear-Gaussian model from the IBP prior with D = 10.