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December 13, 2015 03:19
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Cost update under bandit setting
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| def single_action_cost(self,y): | |
| index=numpy.nonzero(y) | |
| true_cost=y[index] | |
| y = self.output.copy() | |
| cost = T.scalar() | |
| y_update = (y, T.set_subtensor(y[index], cost)) | |
| f = function([cost], updates=[y_update]) | |
| f([true_cost]) | |
| return (y-self.output)**2 |
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