| The online HMC learning procedure |
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| 1. | Start at a
datavector, d, and use backprop to compute |
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| for every
parameter |
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| 2. | Run HMC for many
steps with frequent renewal of the |
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| momentum to get
equilibrium sample, c. Each step |
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| involves a
forward and backward pass to get the |
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| gradient of the
energy in dataspace. |
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| 3. | Use backprop to
compute |
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| 4. | Update the
parameters by : |
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