| 13 |
|
|
|
| Four reasons why learning is impractical |
||
| in Boltzmann Machines |
||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| • | If there are
many hidden layers, it can take a long time to |
|||||||||||||
| reach thermal
equilibrium when a data-vector is clamped |
||||||||||||||
| on the visible
units. |
||||||||||||||
| • | It takes even
longer to reach thermal equilibrium in the |
|||||||||||||
| “negative” phase
when the visible units are unclamped. |
||||||||||||||
| – | The
unconstrained energy surface needs to be highly |
|||||||||||||
| multimodal
to model the data. |
||||||||||||||
| • | The learning
signal is the difference of two sampled |
|||||||||||||
| correlations
which is very noisy. |
||||||||||||||
| • | Many weight
updates are required. |
|||||||||||||