| Avoiding local optima |
|
|
|
|
|
|
|
|
|
|
|
|
| • | EM can easily get
stuck in local optima. |
||||||||||
| • | It helps to
start with very large Gaussians that |
||||||||||
| are all very
similar and to only reduce the |
|||||||||||
| variance
gradually. |
|||||||||||
| – | As
the variance is reduced, the Gaussians |
||||||||||
| spread
out along the first principal component |
|||||||||||
| of
the data. |
|||||||||||