| How to compress document count vectors |
| output |
| vector |
| 2000
reconstructed counts |
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| • | We train the |
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| autoencoder to |
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| reproduce its
input |
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| vector as its
output |
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| • | This forces it to |
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| compress as much |
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| information as
possible |
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| into the 2 real
numbers |
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| in the central
bottleneck. |
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| • | These 2 numbers
are |
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| then a good way
to |
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| visualize
documents. |
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| 500 neurons |
| 250 neurons |
| 2 |
| 250 neurons |
| 500 neurons |
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| Input
vector uses |
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| Poisson
units |
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| 2000
word counts |