 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| • |
Supervised
Learning: this models p(y|x)
|
|
|
– |
Learn
to predict a real valued output or a class label
|
|
|
from
an input.
|
|
| • |
Reinforcement
learning: this just tries to
have a good time
|
|
|
– |
Choose
actions that maximize payoff
|
|
| • |
Unsupervised
Learning: this models p(x)
|
|
|
– |
Build
a causal generative model that explains why
|
|
|
some
data vectors occur and not others
|
|
|
or
|
|
|
– |
Learn
an energy function that gives low energy to data
|
|
|
and
high energy to non-data
|
|
|
or
|
|
|
– |
Discover
interesting features; separate sources that
|
|
|
have
been mixed together; find temporal invariants etc.
|
|
etc.
|
|